Von Berg, George Botha ACCURACY OF POLYETHER VS PLASTER IMPRESSIONS FOR LONG-SPAN IMPLANT SUPPORTED PROSTHESES MSc (Dent) Wits 2007 ACCURACY OF POLYETHER VS PLASTER IMPRESSIONS FOR LONG-SPAN IMPLANT SUPPORTED PROSTHESES George Botha von Berg A research report submitted to the Facu lty of Health Scie nces, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of MSc (Dent) Johannesburg 2007 DECLARATION I, George Botha von Berg, hereby declare that this dissertation is my own work. It is being submitted for the degree of MSc (Dent) at the University of the Witwatersrand, Johannesburg. It has not been submitted before for any degree or examination at this or any other University. Signed by: ??????????????.. George Botha von Berg On this?????? day of????????? 2007 ii To my father, Dudley Albert von Berg, who co mpleted his BSc at the University of the Witwatersrand during the difficult post-war years, and an MSc at the same institution during the 1960s. iii ABSTRACT Two different implant impression materials viz. a polyether (Impregum ?) and a plaster (Plastogum ?) impression material were used and compared with respect to the accuracy with which abutment positions were reproduced from a stainless steel master model containing five implant analogues. Ten polyether impressions and ten plaster impressions were taken and cast in stone. The positions of the precision impression copings on the twenty impressions were meas ured using a Reflex Microscope. The positions of the implant analogues on the twenty casts were also measured and compared to the positions on the stainless st eel master model. Statistical analysis indicated significant differences between the polyether impression and the plaster impression for full arch implant supported pr ostheses. The use of plaster resulted in smaller interabutment error but with less pred ictable variance in dimensions. iv ACKNOWLEDGEMENTS Sincere thanks to the following persons and in stitutions for their contributions to and guidance with this project, Prof Dale Howes Adjunct Professor, Department of Prosthodontics, School of Oral Health Sciences, University of the Witwatersrand, Johannesburg, supervisor of this project for his time and guidance and sincere interest in the project. Prof Hemant Dullabh previously from the University of the Witwatersrand and co- supervisor, for his advice and support. Currently head of Department of Prosthodontics at the University of Pretoria. Prof Fanie Botha, head of the Centre of Stomatologica l Research at the University of Pretoria, for his programming and guidance wi th the use of the Reflex Microscope. Dr Steve Olorunju from the Medical Research In stitute for processing the data statistically. Mr Riaan Fourie from Kara Dental Laboratory, for making impression trays and casting models. Mr. Graham Blackbeard, MD of Southern Implants, for donating implant components and making staff available for assistance. Dr Louis Potgieter, a friend, for giving valuable advice on writing the dissertation. Mrs Ria Potgieter for proofreading the dissertation. Mrs Lee Hofer from 3M/ESPE for donating Impregum Penta with the Pentamix machine. Mr Douglas Patrick from H&P Dental for donating Bosworth Plastogum impression material. Mr Sarel van Staden from SVS Photography for taking photographs. Mrs Loretta Steyn for scanning images. My wife, Lizanda, and my children for their love and supp ort during difficult times. v TABLE OF CONTENTS Page Declaration ii Dedication iii Abstract iv Acknowledgements v Table of Contents vi List of Figures vii 1. Introduction 1 2. Literature Review 2 3. Purpose of the study 11 4. Materials and methods 11 Photographs 16 5. Results 20 Charts: Comparison of Impressions and S-Steel 31 Charts: Comparison of Casts and S-Steel 35 Combined Box Plots with Significance Indication 39 6. Discussion 44 7. Conclusion 49 8. Appendix A 51 9. Appendix B 61 10. References 72 vi LIST OF FIGURES AND TABLES Figure Page 4.1 Ten Measuring Positions 15 4.2 Stainless Steel Master Model 16 4.3 View of stainless steel model with implant analogues numbered 16 4.4 Stainless steel model with precisi on impression copings in place 16 4.5 Acrylic Impression Tray 16 4.6 Inside of Impression Tray 16 4.7 Polyether Impression 16 4.8 Analogue Clamping Device 17 4.9 Southern Torque Wrench 17 4.10 Torquing Impression Coping onto Implant Analogue 17 4.11 Polyether Impression with Implant Analogue in Place 17 4.12 The Reflex Microscope 17 4.13 The Floating 10 ?m Light Spot 17 4.14 Numbering of Copings on Impression 18 4.15 Numbering of Analogues on Cast from polyether 18 4.16 Detail of Plaster Impression 18 4.17 Detail of Cast from Plaster 18 4.18 Position of Light Spot at Tangent to Inner Sides of Coping in Impression 19 4.19 Light Spot at Tangent to Outside of Analogue in Cast 19 5.1 No significant difference for casts and S-S master model 20 5.2 No Significant diff: Impressions 21 5.3 Significant diff. Pl/SS 21 5.4 Significant diff. Imp/SS 22 5.5 Significant diff. Pl/Imp 22 5.6 Discrepancy of Median Measurements of Impressions 23 5.7 Magnitude of Discrepancy for Impressions 24 5.8 No Significant diff: Casts 24 5.9 Significant diff: Pl/SS 25 5.10 Significant diff: Imp/SS 25 5.11 Significant diff: Pl/Imp 25 5.12 Discrepancy of Median Meas urements of Casts 27 5.13 Magnitude of Discrepancy for Casts 27 5.14 Total of Mean Inter-Implant Distances 30 5.15 Charts: Comparison of Impressions and S-Steel Distance 1-2 31 5.16Charts: Comparison of Impressions and S-Steel Distance 1-3 31 vii 5.17 Charts: Comparison of Impressions and S-Steel Distance 1-4 31 5.18 Charts: Comparison of Impressions and S-Steel Distance 1-5 32 5.19 Charts: Comparison of Impressions and S-Steel Distance 2-3 32 5.20 Charts: Comparison of Impressions and S-Steel Distance 2-4 32 5.21 Charts: Comparison of Impressions and S-Steel Distance 2-5 33 5.22 Charts: Comparison of Impressions and S-Steel Distance 3-4 33 5.23 Charts: Comparison of Impressions and S-Steel Distance 3-5 33 5.24 Charts: Comparison of Impressions and S-Steel Distance 4-5 34 5.25 Charts: Comparison of Casts a nd S-Steel Distance 1-2 35 5.26 Charts: Comparison of Casts and S-Steel Distance 1-3 35 5.27 Charts: Comparison of Casts a nd S-Steel Distance 1-4 35 5.28 Charts: Comparison of Casts and S-Steel Distance 1-5 36 5.29 Charts: Comparison of Casts and S-Steel Distance 2-3 36 5.30 Charts: Comparison of Casts and S-Steel Distance 2-4 36 5.31 Charts: Comparison of Casts a nd S-Steel Distance 2-5 37 5.32 Charts: Comparison of Casts and S-Steel Distance 3-4 37 5.33 Charts: Comparison of Casts a nd S-Steel Distance 3-5 37 5.34 Charts: Comparison of Casts and S-Steel Distance 4-5 38 5.35 Combined Box Plots with Significance Indication 1-2 39 5.36 Combined Box Plots with Significance Indication 1-3 39 5.37 Combined Box Plots with Significance Indication 1-4 40 5.38 Combined Box Plots with Significance Indication 1-5 40 5.39 Combined Box Plots with Significance Indication 2-3 41 5.40 Combined Box Plots with Significance Indication 2-4 41 5.41 Combined Box Plots with Significance Indication 2-5 42 5.42 Combined Box Plots with Significance Indication 3-4 42 5.43 Combined Box Plots with Significance Indication 3-5 43 5.44 Combined Box Plots with Significance Indication 4-5 43 6.1 Casts vs. S-Steel 44 6.2 The Passive Abutment (courtesy of Southern Implants) 47 6.3 Passive abutment illustration (cou rtesy of Southern Implants) 48 Table 5.1 Total of Mean Distances (mm) 29 5.2 Expansion relative to Stainless-steel 29 viii 1. INTRODUCTION Osseointegrated implants are a successful way of replacing missing teeth with long- term reliable restorations, whether for singl e teeth, partial or full arch prostheses. During the trial fitting of a long span prosthesis, the framework often does not fit passively. This may transfer detrimental or even harmful forces onto the implant-bone interface, resulting in compli cations, including loss of marginal bone and integration, framework fracture and gold scre w loosening. It is thus impe rative to find the most accurate way of transferring th e information from a patient's mouth to a master model on which the prosthesis will be manufactured. Techniques for perfecting the precision of fit of the prosthesis have not been fully mastered in dentistry and therefore various impression and manufacturing techniques have been employed by various authors. The passive fit of the implant-borne metal fr amework is a prerequisite to minimise the above-mentioned complications. Authors have made use of various impre ssion techniques to accomplish a passive-fit. 20- 22 Some studies find no difference between various impression techniques while other studies indicate a significant difference. 21-28, 30, 31 The use of plaster as an impression material has been recommended in some studies in order to eliminate the potential for error in contrast to usin g elastomeric impression materials. 1 2. LITERATURE REVIEW It has been shown that dental implants have a very good prognosis over a long period of time, with predictable results especially for full arch prostheses in edentulous jaws. 1-14 The first edentulous patients were treated in 1965. 1 Since then, a number of clinical complications have been described. 2 Gold screw fracturing and screw loosening were more frequent in prostheses which were supported by only two implants in partially edentulous restored cases. Even though impl ants can be used in short-span bridges, 3 fewer complications occurred with the use of more implants supporting a prosthesis . 4 Iglesia and Moreno 15 describe passive fit as the ?circumferential and simultaneous contact of all the abutments on their respective implants, a nd of all the gold cylinders of the prosthesis on th eir respective abutment s. ? The authors made a plaster key that splinted the abutments, and when tightened in the absence of passive fit, the plaster fractured. Factors affecting the accuracy of fit begin with the im pression techniques and materials. Comparing the accuracy of polyether impression material with plaster for long span implant supported prostheses is one of many factor s that have been considered to make the metal framework of such prostheses more passive fitting in order to eliminate stress on the components. 28, 38 Elastomeric materials have been used traditionally, while plaster is a stable and accurate material, and therefore a possible choice for accurate reproduction of implant position. 2 1 . Importance of a passive fit: i) Mechanical response It is important to achieve a passive fit between components in order to eliminate mechanical failures which may include screw and abutment loosening or fracture, or fracturing of either the prosthesis or implants. 12, 16 There may be reasons for failure other than the non-pass ive fit of components. Lekholm et al. 9 found that most failing implants were related to implant length and poor maxillary bone quality. Zarb and Schmitt 10 suggest that clinical st ress loading, for example parafunction, may lead to loosening or fracturing of screws. Scre w fracture normally follows screw loosening, the cause of which was difficult to establish. 13 During the try-in stage of the metal framework it was found that the level of static stresses caused by fit discrepancies is de pendent on the shape and location of the gap(s), interabutment distance, and the shape, dimensions, and the rigidity of the metal of the superstructure. 17 There is a positive relationship between the size of the fit discrepancy and the magnitude of stress on the superstructure. The preload (tension due to tightening) in the gold screw is used to bring the mating surfaces closer together, which makes the screw vulnerable to fatigue fractures and loosening. Kan et al. 18 described various clinical methods to evaluate implant framework fit. 3 ii) Biological response Bone response may lead to non-integration or crestal bone loss around the implant. A study by Jemt and Book 5 shows that none of the prostheses presented had a completely passive fit to the implant, with a maximum three-dimensional distortion of 275 ?m, and a mean marginal bone loss of 0.5 and 0.2 mm for the 1-year and 5-year groups respectively. They concluded that ther e had to be a certai n biological tolerance for misfit. Another finding was that no orthodontic bone remodelling took place around the implants due to these forces i nduced by the misfit, although Jemt and Lekholm 8 found bone deformation resulted between im plants that were subjected to an ill-fitting framework. Therefore stress introduced into the implant system may still be present years after prosthesis placement. Strain gauges attached to an abutment indicated that a significant force was introduced on the implant when a fixed prosthesis was connected. 6 The authors found that a greater tension/compression load on the implant was introduced by a fixed prosthesis compared to that of an overdenture. A poor fit could hence introduce tremendous stre sses in the system which may lead to implant failure or metal fatigue fractures . Generally, more problems were found in maxillae compared to mandibles. 7 Jemt and Lekholm 8 refer to dynamic and static loading: dynamic forces arise due to chewing, and static loading is the result of tension in the tightened gold screws of an ill-fitting framework. 4 2. Factors influencing passive fit: a). General Regardless of some problems lik e improper implant placement 11 and bending overload, 12 the predictability of Br?nemark implants has been confirmed. 1 3 Jemt and Lie 19 suggest that distortion is significantly higher in the maxillary arches due to the curvature of the implant arch a nd larger number of implants usually placed in the maxilla. It may also be related to increased alloy content in the castings and poor alignment of implants. b). Impressions i) Impression technique The next factor that contributes towards the precision of the prosthesis is the impression procedure. The procedure may be affected by the technique (open tray or closed tray) to be used. The impression t echnique comprises using square direct or tapered indirect transfer copings. 20 Numerous studies were done where the square impression copings were either splinted or left unsplinted. 20-31 Some square transfer copings were splinted with Durala y or another acrylic resin, with 21 or without reinforcement with dental floss, or reinforced with carbon steel pins, 22 steel burs 23 or orthodontic wire. 24 Vigolo at al. 25,26 used square impression copings sandblasted and coated with the adhesive recommended by the manufacturer of the impression material. They found this technique highly successf ul, providing greater accuracy. Goll 23 used gold cylinders as transfer copings, splinted wi th Duralay, reinforced with steel burs and covered with impression plaster. He reco mmends machined componentry because they are more accurately manufacture d. Assif, Marshak and Schmidt 27 splinted the transfer 5 copings directly to an acrylic resin custom tray. Copings splinted to each other with resin proved to be more accurate than the custom tray method. Assif et al. 28 also found that using autopolymerizing acrylic resin proved to be significantly more accurate than dual-cure acrylic resin as a sp linting material. It was found by Philips et al. 29 that tapered copings may distort th e impression material upon removal. Carr 20 also found the direct transfer method to be the most accurate due to the deformation of impression material with the indirect method. The results of the above-mentioned studies were not conclusive on whether the impression copings should be splinted 22, 23, 25 - 28 or not 21, 24, 30, 31 . ii) Impression materials. The selection of the most accurate impression material is the objective of this study. Traditionally there are six di fferent types of impression ma terials in dentistry: agar hydrocolloid (reversible ), alginate hydrocolloid (irreversible), polysulphide rubber, condensation-cured silicone rubber, addition-cured silic one rubber, and polyether rubber. 32 This study, will however, concentrate on a seventh material, i.e. impression plaster. A study done by Linke, Nicholls and Faucher 32 shows that all materials tested produced casts with an arch perimeter larger than the standard reference model. The reversible hydrocolloid show ed the least interabutment di stortion and the irreversible hydrocolloid the most distortion. It app ears logical that reversible hydrocolloids should be used, but they are seldom used today due to the technique?s sensitivity and equipment requirements. 6 It has been proved by Finger and Ohsawa 33 that different impression materials have different setting contraction va lues. A study was done by Wee 34 to determine the amount of torque required to rotate a squa re impression coping in an impression. He also compared dimensional accuracy among various groups of impression materials with a travelling microscope. Polyethe r was found to produce the highest overall torque values and was significantly more accurate. This was followed by addition cured silicone and polysulphide materials. The casts made from polyethers and addition cured silicones were significantly more accurate than casts made from polysulphide impression mate rial. The use of either polyether or addition cured silicone impression material is therefore recommended for direct implant impressions. The high dimensional stability and coping torque of polyether has made it the impression material of choice for taking impressions for full arch implant supported prostheses. 34 Comparing addition cured si licone (AS), condensati on cured silicone (CS), polysulphide (PS), and polyeth er (PE), Johnson and Craig 35 found that AS showed the smallest change in vertical dimension, AS and CS had the best recovery from undercuts, and AS and PE were the least a ffected by delays in pouring time. Ak?a and ?ehreli 36 found no difference between the results of Impregum, (a polyether), and Panasil, (a polyvinylsiloxane). A combination of silicone impression material and impression plaster was described by Eid 37 , and a combination of polyether and plaster was described by Inturregui et al. 38 , where the polyether alone resulted in the closest duplication of the master cast. Impression plaster and irreversib le hydrocolloid were 7 also combined by Nissen et al. 39 in partially edentulous pa tients. Plaster was used to splint the transfer c opings. Assif et al. 28 also found plaster to be the impression material of choice in completely edentulous patients, since, in their opinion, it is less time-consuming and cheaper. iii) Impression Trays Tautin 40 used a rigid thermoplastic impression tray which was manufactured in the patient's mouth from softened modelling compound. According to Johnson and Craig 41 a custom tray is the impression tray of choice. Moseley and co-workers 42 predicted the maximum stress that the impression tray encountered during rem oval of a complete impression from the oral cavity. For autopol ymerizing polymethyl methacrylate resin trays the yield strength is sufficiently high to safely assume that the tray will not distort under removal forces. In thei r study, Eames and co-workers 43 constructed trays with 2, 4, and 6 mm space for impression materi al and found that the 2 mm spacing provided greater overall accuracy for polyether. iv) Casting of impressions. Casting of the impressions may be in fluenced by humidity and temperature, water/powder ratio, amount of vi bration and spatulation used. 44 v) Component tolerances. Machining tolerances between implant compone nts should also be considered. Ma et al. 45 conclude that machining tolerance determ ines the degree of movement that is 8 possible between paired components. Tole rances exist between abutment, impression coping, stainless steel abutment replicas, and gold cylinder. To ensure an intimate fit, there is always an inherent machining tole rance between the connecting surfaces. The two factors that contribute to machining tolerances are dimensional variation and surface roughness. The tolerances measured between the abutment and gold cylinder were 23.1 ?m, and those between the stainle ss steel abutment replica and gold cylinder were 37.1 ?m. These values were found to be significantly different (P<0.05) which indicates that a passive fit obt ained in the laboratory may not guarantee a passive fit in- vivo, as the passive fit in the laboratory may be outside th e tolerance range of the in- vivo components. Hecker and Eckert 46 found that the machining tolerance of the stainless steel analogue and gol d cylinder was significantly la rger compared with that of the abutment and gold cylinder. This may cause a prosthesis that appears to fit in the laboratory to have a misfit of greater proportion in the clinical setting. Southern Implants, which were used in this study, have a com ponent tolerance of 0.01 mm for critical implant components like the hex of an implant. The 2.7 mm wide hex could be 2.69 to 2.71 mm. It has a tolerance of 0.05 for non critical components like the length of an impression coping for instance. c). Framework manufacturing As far as manufacturing of the metal framew ork is concerned, the computer assisted design/computer assisted manufacturing (CAD/CAM) procedure uses machined and laser-welded titanium frameworks which ar e manufactured by copy milling sections of an acrylic resin framework pattern in grad e 2 titanium and then laser welding the 9 sections together. 47 Jemt et al. 48, 49 found that the welded tita nium frameworks are as accurate as gold alloy castings in a fixed prosthesis. Takahashi and Gunne 50 found the fit of the Procera system, produced by the CAD/ CAM technique, to be significantly better than that of frameworks made with a cast gold alloy. After studying six implant systems, Lang and co-workers 51 found that the CAD/CAM pr oduced Procera abutment should be considered for universal application. When frameworks don't fit passively they need to be sectioned a nd indexed with self- curing acrylic. Of the index materials available, Cho and Chee 53 found that G.C. Pattern resin has a comparable accuracy to Duralay acrylic resin, but has a setting time of only three minutes compared to Duralay?s seven minutes, which saves operating time. Mojon et al. 54 also compared two index materials: Duralay resin had a volumetric shrinkage of 7.9% and Palavit G. resin 6.5%, compared to the 21 % shrinkage of pure methylmethacrylate. The authors also analyzed the influence of powder-to-liquid ratio on dimensional change of the index material and found that adding more liquid to the mix increased shrinkage. d). Mandibular flexure Hobkirk and Schwab 52 found that mandibular deformation of up to 420 ?m can be encountered upon jaw opening, which should be considered both when taking an impression and during placement of a mandibular fixed prosthesis. 10 3 . PURPOSE OF THE STUDY The purpose of this study was to compare the dimensional accuracy of polyether and plaster impressions, and their re sultant casts when compared to a stainless steel master model. The null hypothesis is that there is no di fference between polyether and plaster impression materials relative to the master model. 4. MATERIALS AND METHODS Testing Device A stainless steel plate containing 5 stai nless steel implant analogues (LS12, 3.75 mm, Southern Implants, Irene, South Africa) was used as a master model for impression taking (Fig. 4.2). The model repres ented an occlusal arch with five implants for a full arch implant supported prosthesis. The analogues were fixed by machine pressing into the baseplate and retained in the model by small locknuts preventing any rotation. The analogues were numbered 1 through 5 fr om left to right (Fig. 4.3). Implant analogues numbers 2 and 4 were placed at an 8? lingual inclination to represent the clinical situation. Pr ecision impression copings (CB12P, Southern Implants) were used which were torqued down onto the model to 10 Ncm (Fig. 4.4) before impression taking. 11 Impression taking Standard acrylic impression trays (Fig. 4.5, 4.6) were manufactured (Excel Special Tray Material, Wright Health Group Ltd) on a template over the baseplate to ensure standardization of size and shape and a 2 mm spacing under the trays. 40-43 Windows were cut into each tray to expose the tran sfer copings and guide pins. The windows were covered by a single layer of pink baseplate wax. (Kemdent no 4, Associated Dental Products, Swindon, UK) The trays were left to cure for 24 hours before impression taking. Ten polyether impressions (Impregum ?, Pentamix Lot 202589, exp 2007-03, 3M ESPE, AG Seefeld, Germany) and ten plaster impressions (Plastogum ?, Harry J. Bosworth, Lot 0309-492, exp 2006-09, Skokie, Illinois) were ta ken of the master model complying with the manufacturers? inst ructions for use. ESPE polyether adhesive (Lot 126976, exp2005-02) was used for the Impregum im pressions. Two coats were put on the trays, separated by 15 minute?s drying time. The ten polyether impressions were firs t taken with the 50 available precision impression copings (Fig. 4.7). Measurements of the polyether impressions (Fig. 4.14) were done on the Reflex Microscope be fore their stone casts were poured and measured. Once the casts had been made, the same 50 impression copings were used to take the ten plaster impressions (Fig. 4.16). First the plaster impressions were measured under the Reflex Microscope, and then their respectiv e stone casts were poured and measured. 12 Impressions were taken in a controlled e nvironment with temperature ranging from 19.5 ?C to 20.3 ? C for the polyether impr essions, measured with a Supco THC 200 hygrometer. The values during plaster impr ession taking were 20.5?C to 22.2?C. The temperature ranges differed between the tw o impression materials as polyether and plaster impressions were taken on different da tes. The reason for this was that the stone casts of the polyether impressions had to be made first. Only then could the same 50 impression copings be used for the plas ter impressions. It is unknown to what degree the measurements were affected by this small difference in temperature. The impression materials were mixed according to the manufacturers? recommendations and left for at least 15 minutes before removal from the master model. After removal of the impressions, stainless steel impl ant analogues (LS12, Southern Implants) were atta ched to the precision impre ssion copings. This was done without disturbing the impression copings in the impression by holding the analogue in a clamping device (Fig. 4.8), and torquing the two components to 10 Ncm with a Southern Implant torque wrench (Figs. 4.9, 4.10 and 4.11). Casts were poured in stone, namely Pemaco-CD Peach (Pemaco Incorpor ated, St Louis, MO, USA) according to manufacturer specifications under normal laboratory conditions (Figs. 4.15 and 4.17). 13 Measurements Measurements of the polyether and plaster impressions, and the respective casts were taken on the Reflex Microscope (Refle x Measurement Ltd., Greenways, Ditcheat, Somerset, UK) (Fig. 4.12). The Reflex Microscope is an op tical plotter which measures to an accuracy of 1 ?m. It is li nked directly to a microcomputer and allows direct three-dimensional m easurement (x, y, and z-plane ) of irregularly shaped objects up to 100 mm maximum dimensions. A small di ameter light spot which can be set at 20 ?m, 10 ?m or 5 ?m size appears in the field of view (Fig. 4.13). It is mainly used to calculate linear dimensions between two points. It gi ves an operator measurement error of less than 0.2 mm for linear distan ces, and a mean undermeasurement of 0.28%, which compares favourably with other measuring devices (Speculand, Butcher, Stephens 55 ). The x and y planes are determined by moving th e object table to the left and right, or forwards and backwards. The z-plane is de termined by moving the ocular piece up or down, which brings the object into focus in the same plane as the light spot. During measurement temperature ranged from 21.8 ? C to 26.2?C. The temperature range has no significant effect on the master model as the thermal expansion coefficient of stainless steel is equal to 10 -5 / oC. Measurements of the master and stone models were made on the top corners of the hex of the analogues. The 10 ?m light spot was placed at a tangent to the outermost edge. (See Fig. 4.19). Similarly, when measuring the impressions, the light spot was placed 14 at a tangent to the innermost corner of the precision impression coping which coincides with the position of the analogue?s outermost corner (Fig. 4.18). Each impression and each cast was measured three times, from which a mean value was calculated. The stainless-steel master model was measured 30 times to ensure consistency during the experiment. Distances were compared between the polyether impression, plaster impression and the master model for specific positions, and also between the different casts and the master model. These are the 10 measurements of the inter- implant distances (taken 3 times each) that have been taken for polyether and pl aster for both impressions and casts: Group 41:1-2 Group 42: 1-3 Group 43:1-4 Group 44:1-5 Group 45:2-3 Group 46:2-4 Group 47:2-5 Group 48:3-4 Group 49:3-5 Group 50:4-5 Fig. 4.1 Ten Measuring Positions 15 PHOTOGRAPHS 3 4 2 1 5 Figure 4.2 Stainless Stee l Master Model Figure 4.3 View of Stainless Steel Model with Implant Analogues Numbered Figure 4.4 Stainless Steel Model with Figure 4.5 Acrylic Impression Tray Precision Impression Copings in Place Figure 4.6 Inside of Impression Tray Figure 4.7 Polyether Impression 16 Figure 4.8 Analogue Clamping Device Figure 4.9 Southern Torque Wrench Figure 4.10 Torquing Impression Coping Figure 4.11 Polyether Impression with onto Implant Analogue Implant analogue in Place Figure 4.12 The Reflex Microscope Figure 4.13 The Floating 10 ?m Light Spot 17 Figure 4.14 Numbering of Copings Figure 4.15 Numbering of Analogues on Impression on Cast from Polyether Figure 4.16 Detail of Plaster Impression Figure 4.17 Detail of Cast from Plaster 18 Measuring Positions: Figure 4.18 Position of Light Spot at Tangent Figure 4.19 Light Spot at Ta ngent to to Inner Sides of Coping in Impression Outside of Analogue in Cast 19 5. RESULTS Methodology The data was analyzed using descriptive stat istics and the use of ANOVA (Analysis of Variance) to compare polyether , plaster and the stainless st eel (SS) model, for both the impressions and their resultant casts. Results General A two-way ANOVA was used to compare the ca sts from polyether impression material and the casts from plaster impression material with respect to the distances between the five implant analogues. The results indicate that there is a signif icant difference among the two impression materials and the SS m odel. Significant differences also exist among their resultant casts and the SS model for all but one of the interimplant distances. The only exception is the result for the casts of group 46 which relates to the distance between implants 2-4 (p = 0.4836) (F ig. 5.1). This is the only group where there is no significant difference among a ll three measured models, i.e. the two different casts and the stainless steel master. This group do, however, show a significant difference. Fig 5.1 No significant difference for casts and SS master model 20 Variability The results show considerable variability within and between the samples. The polyether impressions and casts show a greate r consistency than the plaster impressions and casts, although significantly differen t from the stainless steel model. Even though the measurements for plaster are more inconsistent than for polyether, generally the mean plaster va lues approximate the stainless steel values more closely than the polyether values do. A. Impressions: a) No significant diffe rence (p>0.05) between: 21 Plaster/SS Polyether/SS Plaster/Polyether Fig. 5.2 No Significant diff: Impressions b) Significant difference (p<0.05) Significant differences were found in the following areas: Plaster/SS Fig. 5.3 Significant diff. Pl/SS 22 Polyether/SS Fig. 5.4 Significant diff. Imp/SS Plaster/Polyether Fig. 5.5 Significant diff. Pl/Imp i) Plaster/SS Plaster and stainless steel di ffer significantly (p<0.05) in a ll but one area: i.e. group 45 (2-3). (Figs. 5.1, 5.2 & 5.3). ii) Polyether/SS Polyether and stainless steel differ signifi cantly (p<0.05) in all cases. (Figs.5.2 & 5.4). iii) Plaster/Polyether Plaster and polyether differ signi ficantly (p<0.05) in all but three areas: i.e. groups 41 (1-2), 43 (1-4) and 50 (4-5 ). (Figs. 5.2 & 5.5). The largest P-value (0.972) is found in gr oup 43 (1-4) between plaster and polyether. This indicates the least significant difference as can also be seen in the line graph in Figure 5.17 where the two lin es are closely spaced. In Figure 5.18 (group 44; 1-5) the plaster and polyether lines can be seen on either side of the stainless-steel line. Over this longest distance on the model it seems that the plaster impression has contracted and the pol yether expanded relative to the SS model. Though there is still evidence of statistical significance observed in group 43, the one for Group 44 gives a more serious evidence of difference. Relatively therefore, observed difference in Group 43 is less than that for Group 44. The chart below (Fig. 5.6) Discrepancy of Median Measurements of Impressions, indicates the discrepancy between the tw o impression materials compared to the stainless steel model. Discrepancy of Median Measurements of Impressions - 0 . 4 - 0 . 2 0 0 . 2 0 . 4 0 . 6 0 . 8 1 1 . 2 M 1 - 2 M 1 - 3 M 1 - 4 M 1 - 5 M 2 - 3 M 2 - 4 M 2 - 5 M 3 - 4 M 3 - 5 M 4 - 5 Measurements between Implants D is cr ep an cy (m m ) Polyether - SS Plaster - SS Fig. 5.6 Discrepancy of Median Measurements of Impressions 23 The width of the lines in Figure 5 .7 refl ects the magnitude of the discrepancy in relation to its posit ion on the model. Fig 5.7 Magnitude of Discrepancy for Impressions Polyether-SS expansion Plaster-SS expansion contraction contraction B. Casts: a) No significant diffe rence (p>0.05) between: 24 Plaster/SS Polyether/SS Plaster/Polyether Fig. 5.8 No Significant diff: Casts 25 b) Significant difference (p<0.05) Significant differences were found in the following areas: Plaster/SS Fig. 5.9 Significant diff: Pl/SS Polyether/SS Fig. 5.10 Significant diff: Polyether/SS Plaster/Polyether Fig. 5.11 Significant diff: Plaster/Polyether i) Plaster/SS Plaster and stainless stee l differ significantly (p<0.05) in all but three areas: i.e. group 44 (1-5), 45 (2-3) and 46 (2-4). (Figs. 5.8 & 5.9). 26 ii) Polyether/SS Polyether and stainless steel differ significan tly (p<0.05) in all but one area: i.e. group 46 (2-4). (Figs. 5.8 & 5.10). iii) Plaster/Polyether Plaster and polyether differ si gnificantly (p<0.05) in all but two areas: i.e. group 46 (2- 4) and 48 (3-4). (Figs. 5.8 & 5.11.) The line graphs for group 46 (2-4) (Fig. 5.30) and group 48 (3-4) (Fig. 5.32) are the only graphs where the values for the polyether casts are smaller than the stainless steel model (contractive distortion). In all the other graphs both the polyether and plaster lines lie above the stainless steel line, de picting expansive distortion, with polyether casts having a larger degree of expa nsive distortion than plaster casts. This contraction for (2-4) and (3-4) is also depicted in Fig. 5.12 Discrepancy of Median Measurements of Casts. The discrepancy between the casts of the two impression materials compared to the stainless steel model is illustrated in the graph below (Fig. 5.12). Discrepancy of Median Measurements of Casts - 0 . 2 0 0 . 2 0 . 4 0 . 6 0 . 8 1 1 . 2 1 . 4 M 1 - 2 M 1 - 3 M 1 - 4 M 1 - 5 M 2 - 3 M 2 - 4 M 2 - 5 M 3 - 4 M 3 - 5 M 4 - 5 Measurements between implants D is cr ep an cy (m m ) Polyether - SS Plaster - SS Fig. 5.12 Discrepancy of Median Measurements of Casts The weight of the lines in Fig 5.13 reflect th e magnitude of the discrepancy in relation to its position on the model. Fig. 5.13 Magnitude of Discrepa ncy for Casts Polyether-SS expansion Plaster-S expansion contraction contraction 27 28 F-value The F-value it is another statistical test to determine significance. Definition of F value: The ANOVA procedure employs the statistic (F) to test the statistical significance of the differences among the obtained means of two or more random samples from a given population. Us ing the Central Limit Theorem, one calculates two estimates of a population variance. (1). An estimate in which the s square of the obtained means of the several samples is multiplied by n (the size of the samples). (2). An estimate that is calculated as the average (mean) of the obtained s squares of the several samples. The statistic value (F) is formed as the ratio of (1) over (2). If this ratio is sufficiently larger than 1.0, the observed differences among the obtained means are described as being statistically significant. For the casts, all 10 groups have fairly high F values (ranging from 9.69 to 1282.07) except for group 46 which has a value of less th an 1 (0.51). The large F values indicate that the plaster and polyether impression mate rials do provide signifi cant differences in the casts that they produce. The exception is group 46. (Implant 2-4) 29 Total Inter-Implant Distances The following table (5.1) depicts the Total Distances when the 10 various distances (mean values) are added together. Table 5.1 Total of Mean Distances (mm) Polyether Plaster S-Steel Impres s io ns 282.9 0 282.1 0 2 7 8 . 7 4 C as t s 284.0 4 281.3 1 2 7 8 . 7 4 From these values were calculated the diffe rences and the percentage of expansion compared to the stainless-steel model as show n in table 5.2. It is not iceable that for the resultant casts the percentage expansion for polyether is double that of plaster. Table 5.2 Expansion relative to Stainless-steel Polyether: mm % exp Polyether Plaster: mm % exp Plaster Impres s io ns 4.17 1. 4 9 3 . 3 7 1 . 2 1 Casts 5.30 1. 9 0 2 . 5 7 0 . 9 2 The chart below of Total of Mean Inter-imp lant Distances (Fig. 5.14) reflects the sum of all the mean individual inter-implant measurements. This shows over the total dist ances that casts from polyeth er showed more expansive distortion than casts from plas ter. In fact, the casts from plaster underwent contraction in relation to their impressions. Total of Mean Inter-Implant Distances 286.00 284.00 M ill im et re s Casts282.00 Impressions 280.00 S - S t e e l Control 278.00 276.00 Polyethe r Plaste r Material Fig 5.14 Total of Mean Inter-Implant Distances 30 CHARTS: COMPARISON OF IMPRESSIONS AND S-STEEL Comparison of Impressions for distance 1_2 13. 0 13. 5 14. 0 14. 5 15. 0 15. 5 1 2 3 4 5 6 7 8 9 10 Impressions D is ta nc e (m m ) Im pregum P l as t er S -S t eel Fig.5.15 Group 41 Comparison of Impressions for distance 1_3 29. 5 30. 0 30. 5 31. 0 31. 5 1 2 3 4 5 6 7 8 9 10 Impressions D is ta nc e (m m ) Im pregum P l as t er S -S t eel Fig.5.16 Group 42 Comparison of Impressions for distance 1_4 39. 8 40. 0 40. 2 40. 4 40. 6 40. 8 41. 0 1 2 3 4 5 6 7 8 9 10 Impressions D is ta nc e (m m ) Im pregum P l as t er S -S t eel Fig.5.17 Group 43 31 Comparison of Impressions for distance 1_5 46. 9 47. 0 47. 0 47. 1 47. 1 47. 2 47. 2 47. 3 47. 3 1 2 3 4 5 6 7 8 9 10 Impressions D is ta nc e (m m ) Im pregum P l as t er S -S t eel Fig.5.18 Group 44 Comparison of Impressions for distance 2_3 16. 8 16. 9 17. 0 17. 1 17. 2 17. 3 1 2 3 4 5 6 7 8 9 10 Impressions D is ta nc e (m m ) Im pregum P l as t er S -S t eel Fig.5.19 Group 45 Comparison of Impressions for distance 2_4 30. 1 30. 1 30. 2 30. 2 30. 3 1 2 3 4 5 6 7 8 9 10 Impressions D is ta nc e (m m ) Im pregum P l as t er S -S t eel Fig.5.20 Group 46 32 Comparison of Impressions for distance 2_5 39. 7 39. 8 39. 9 40. 0 40. 1 40. 2 40. 3 40. 4 40. 5 1 2 3 4 5 6 7 8 9 10 Impressions D is ta n ce (m m ) Im pregum P l as t er S -S t eel Fig.5.21 Group 47 Comparison of Impressions for distance 3 _ 4 15. 8 16. 0 16. 2 16. 4 16. 6 16. 8 1 2 3 4 5 6 7 8 9 10 Impressions D is ta nc e (m m ) Im pregum P l as t er S -S t eel Fig.5.22 Group 48 Comparison of Impressions for distance 3 _ 5 29. 0 29. 2 29. 4 29. 6 29. 8 30. 0 30. 2 30. 4 1 2 3 4 5 6 7 8 9 10 Impressions D is ta nc e (m m ) Im pregum P l as t er S -S t eel Fig.5.23 Group 49 33 Comparison of Impressions for distance 4 _ 5 12. 5 13. 0 13. 5 14. 0 14. 5 15. 0 1 2 3 4 5 6 7 8 9 10 Impressions D is ta nc e (m m ) Im pregum P l as t er S -S t eel Fig.5.24 Group 50 34 CHARTS: COMPARISON OF CASTS AND S-STEEL Comparison of Casts Types for distance 1_2 13. 0 13. 5 14. 0 14. 5 15. 0 15. 5 1 2 3 4 5 6 7 8 9 10 Casts D is ta n ce s (m m ) Im pregnum P l as t er S -S t eel Fig.5.25 Group 41 Comparison of Casts Types for distance 1_3 29. 5 30. 0 30. 5 31. 0 31. 5 1 2 3 4 5 6 7 8 9 10 Casts D is ta n ce ( m m ) Im pregnum P l as t er S -S t eel Fig.5.26 Group 42 Comparison of Casts Types for distance 1_4 39. 8 40. 0 40. 2 40. 4 40. 6 40. 8 41. 0 1 2 3 4 5 6 7 8 9 10 Casts D is ta n ce ( m m ) Im pregnum P l as t er S -S t eel Fig.5.27 Group 43 35 Comparison of Casts Types for distance 1_5 46. 5 47. 0 47. 5 48. 0 48. 5 1 2 3 4 5 6 7 8 9 10 Casts D is ta n ce ( m m ) Im pregnum P l as t er S -S t eel Fig.5.28 Group 44 Comparison of Casts Types for distance 2_3 16. 4 16. 6 16. 8 17. 0 17. 2 17. 4 17. 6 17. 8 1 2 3 4 5 6 7 8 9 10 Casts D is ta n ce ( m m ) Im pregnum P l as t er S -S t eel Fig.5.29 Group 45 Comparison of Casts Types for distance 2_4 29. 6 29. 8 30. 0 30. 2 30. 4 30. 6 30. 8 1 2 3 4 5 6 7 8 9 10 Casts D is ta n ce ( m m ) Im pregnum P l as t er S -S t eel Fig.5.30 Group 46 36 Comparison of Casts Types for distance 2_5 39. 4 39. 6 39. 8 40. 0 40. 2 40. 4 40. 6 40. 8 41. 0 41. 2 1 2 3 4 5 6 7 8 9 10 Casts D is ta n ce ( m m ) Im pregnum P l as t er S -S t eel Fig.5.31 Group 47 Comparison of the Casts Types for distance 3 _ 4 16. 0 16. 2 16. 4 16. 6 16. 8 1 2 3 4 5 6 7 8 9 10 Casts D is ta n ce ( m m ) Im pregnum P l as t er S -S t eel Fig.5.32 Group 48 Comparison of the Casts Types for distance 3 _ 5 28. 5 29. 0 29. 5 30. 0 30. 5 31. 0 31. 5 1 2 3 4 5 6 7 8 9 10 Casts D is ta n ce ( m m ) Im pregnum P l as t er S -S t eel Fig.5.33 Group 49 37 Comparison of the Casts Types for distance 4 _ 5 12. 5 13. 0 13. 5 14. 0 14. 5 15. 0 15. 5 1 2 3 4 5 6 7 8 9 10 Casts D is ta n ce ( m m ) Im pregnum P l as t er S -S t eel Fig.5.34 Group 50 38 COMBINED BOX PLOTS WITH SIGNIFICANCE INDICATION 14 14.5 15 15.5 C a s t Imp re s s i o ns Pla s t er Imp r eg u m S-St ee l Pla s t er Imp r eg u m S- St ee l Fig. 5.35 Group 41 (1-2) in mm 30.4 30.6 30.8 31 31.2 31.4 C a s t Imp re s s i o ns Pla s t er Imp r eg u m S-St ee l Pla s t er Imp r eg u m S- St ee l Fig. 5.36 Group 42 (1-3) in mm 39 40.6 40.4 40.2 40.8 C a s t Imp re s s i o ns Pla s t er Imp r eg u m S-St ee l Pla s t er Imp r eg u m S- St ee l Fig. 5.37 Group 43 (1-4) in mm 47 47.2 47.4 47.6 47.8 48 C a s t Imp re s s i o ns Pla s t er Imp r eg u m S-St ee l Pla s t er Imp r eg u m S- St ee l Fig. 5.38 Group 44 (1-5) in mm 40 17.6 17.4 17.2 17 16.8 17.8 C a s t Imp re s s i o ns Pla s t er Imp r eg u m S-St ee l Pla s t er Imp r eg u m S- St ee l Fig. 5.39 Group 45 (2-3) in mm 30 30.2 30.4 30.6 C a s t Imp re s s i o ns Pla s t er Imp r eg u m S-St ee l Pla s t er Imp r eg u m S- St ee l Fig. 5.40 Group 46 (2-4) in mm 41 40 40.2 40.4 40.6 40.8 41 C a s t Imp re s s i o ns Pla s t er Imp r eg u m S-St ee l Pla s t er Imp r eg u m S- St ee l Fig. 5.41 Group 47 (2-5) in mm 16.2 16.4 16.6 16.8 C a s t Imp re s s i o ns Pla s t er Imp r eg u m S-St ee l Pla s t er Imp r eg u m S- St ee l Fig. 5.42 Group 48 (3-4) in mm 42 29.5 30 30.5 31 C a s t Imp re s s i o ns Pla s t er Imp r eg u m S-St ee l Pla s t er Imp r eg u m S- St ee l Fig. 5.43 Group 49 (3-5) in mm 13.5 14 14.5 15 C a s t Imp re s s i o ns Pla s t er Imp r eg u m S-St ee l Pla s t er Imp r eg u m S- St ee l Fig. 5.44 Group 50 (4-5) in mm 43 6. DISCUSSION The three-dimensional accuracy of two impression materials was investigated with the use of a Reflex Microscope. By studying th e results a few observations were made. It is not possible to make an undistorted im pression or cast. These measurements and the review of the literature shows that it is almost impossible to duplicate the three dimensions from the jaw onto a cast on which a precisely fitting and passive superstructure can be manufactured. It appe ars from this set of results that horizontal dimensions between implant analogues tend to increase with both impression materials. This supports th e findings of Linke et al. 32 . The rationale for using plaster impression material is the limitation of expansive distortion that takes place compared to polyether impressions. The general conclusion from these findings is that plaster creates less distortion, but that the reproduc tion of consistent dimensions is less predictable. The polyether measurements produced a straighter line graph, showing a better consistency over the ten m odels, but greater distortion. No significant difference between: Plaster/SS Polyether/SS Plaster/polyether Fig. 6.1 Casts vs S-Steel 44 Distance 2-4 is the only distance where th ere is no significant difference for both casts and the master model (Fig. 6.1). It is essential to have meticulous inspec tion of laboratory and clinical components during their connection, to preven t avoidable errors in fit wh ich are not inherent to the impression, or laboratory techniques. When looking at the impressions under the Reflex Microscope, the author noticed se veral fibre or dust-like particles on the impression copings in the plas ter impressions. These ha d to be removed with high pressure air spray before the implant anal ogues could be connected to the copings. These particles might have flaked off from the plaster and could make a meaningful difference in the vertical position of the analogue when secured over the debris. Distortion is unpredictable and is determin ed by the site (Figs 5.12 & 5.13). It is likely to be expansive and more so in the an terior-posterior dimension than in a lateral dimension. From Fig. 5.12 it is noticeable that the differences in measurements across the model are negligible. The differences in measurements anterior-posteriorly are much bigger; almost 1 .2 mm for polyether casts from distance 1-2. This may possibly result in a framewor k that is wide enough but too long in the anterior- posterior dimension. Contra ction distortion during the process was found to be less than the expansive distortion resulting in net expansion. The least distortion appears generally to be ac ross the cast. In this case it included the tilted implants. Group 46 (2 -4) recorded a P-value of 0.955 which indicates a non-significant difference between the casts fr om plaster and the S-Steel model. This was the second highest P-value recorded for casts. The highest was 0.996 also for 45 casts from plaster vs. S-S for group 44 (1-5), indicating the least significance of all measurements. Both measurements were across the cast. The casts from polyether were generally bi gger than their impressions (Fig 5.15) by a magnitude of 1.14mm over the total distan ce measured (284.04mm for the casts vs. 282.90mm for their impressions)(Table 5.1). Th at is an expansion of 0.4%. Over the same distance measured the casts from polyether were 5.3mm bigger than the stainless steel model. That is a 1.9% expansion (Table5.2). The casts from plaster, however, were sma ller than their impressions by 0.79mm over the total distance (281.31mm fo r the casts vs. 282.10mm for their impressions). That is shrinkage of 0.28%. The casts from plaster were still larger than the stainless steel model by 2.57mm which is expansion of 0.92%. From this it appears that the amount of expansion for polyether casts is doubl e that of plaster casts which may be significant in the passiv e fit of the framework. As a result of the discrepancies that o ccur using stone casts, current research and development is being directed towards t echniques that eliminated them from the fabrication of the prosthesis. The importance of that is to eliminate the sectioning and luting of the metal framework and thereby having to alter the working model. Sectioning and reassembling the framework is time-consuming and results in a weaker and metallurgically more complex prosthetic framework. The CAD/CAM technique may full-fill this requirement. Images are scanned intraorally or extra orally and frameworks are manufactured from this information. The Procera implant bridge works on this technique. The problem here is that a distorted m odel is scanned which 46 defeats the object. Ideally the implants should be scanned intraorally, but currently that is a technique which is not yet available. Passive abutments are components which may be used in cases where a passive fit cannot be established (Fig. 6.2). With an ill-fitting framework passive abutments can be secured over the implants with a sma ll screw. The framework is subsequently cemented onto the passive abutments. Due to the tolerances that ex ist, the leeway is taken up by cement. Once the cement has set the small screws are removed and the passive abutments will be picked up by th e framework. The whole framework can now be secured onto the implants with the bigger screws. This allows the framework to be screw-retained while discrepancie s are absorbed in the cement (Fig.6.3). Fig. 6.2 the Passive abutment 47 Fig. 6.3 Diagram of passive abutment illust rating its capacity to allow ill-fitting frameworks to be adapted to the implants. Gallucci et al. 56 immediately loaded implants with a provisional restoration in order to minimise "micromotion". In this way, fibrous encapsulation is prevented, and osseointegration results. When the provisional restorati on was removed on a fortnightly basis, screw loosening was found in all patients after the first removal of the prosthesis, but no screw loosening was found 15 days later. It appears that, if the implants are splinted with no tension on them, the normal complications with ill- fitting prostheses are prevented. However, Jemt and Book 5 disagree, and state that no orthodontic adjustment takes place around osseointegrated implants with stress introduced on them. Hoshaw, Brunski and Cochran 57 concluded that there was an 48 increased bone modelling response at the pe riosteal surface near loaded implants. Further study in this field is necessary. 49 7. CONCLUSION Under the conditions of this study the following conclusions can be drawn with respect to distortion of implant analogue positions on the master cast: 1. The null hypothesis is rejected as there is a significant difference between models made using polyether impression material compared to those made with plaster impression material. 2. Plaster impression material results in less expansion of the cast, but in more variance with less predictability. 3. As a result of this finding, plaster impression material should be considered for full arch implant supported prostheses. 4. Digital intraoral scanning of the implants may be the future solution for more accurate reproduction of implant positions. 5. A plaster free technique may be consider ed where a passive cementation matrix is used. The cementation matrix is screwed onto the implants, luted together and taken off. Implant analogues are connected to the cemen tation matrix and attached to each other without using plaster. Theore tically no distortion takes place. 50 8 . APPENDIX A TABLE OF MEANS IMPRESSIONS . anova distance type model type* model if group==41 Number of obs = 90 R-squared = 0.9938 Root MSE = .046197 Adj R-squared = 0.9908 Source | Partial SS df MS F Prob > F -----------+---------------------------------------------------- Model | 20.5522996 29 .708699986 332.08 0.0000 | type | 20.104063 2 10.0520315 4710.10 0.0000 model | .145838885 9 .016204321 7.59 0.0000 type*model | .302397676 18 .016799871 7.87 0.0000 | Residual | .128048584 60 .002134143 -----------+---------------------------------------------------- Total | 20.6803482 89 .232363463 . table type model if group==41, c(mean distance n distance sd distance) format(%7.2f) -------------------------------------------------------------------------------- | model typelbl | 1 2 3 4 5 6 7 8 9 10 ----------+--------------------------------------------------------------------- Impregum | 15.12 15.16 15.00 14.96 15.04 15.03 15.00 15.05 15.05 15.04 | 3 3 3 3 3 3 3 3 3 3 | 0.01 0.00 0.02 0.08 0.02 0.02 0.02 0.01 0.05 0.01 | Plaster | 15.10 14.90 15.04 14.99 14.77 15.12 15.11 15.12 15.10 15.07 | 3 3 3 3 3 3 3 3 3 3 | 0.01 0.14 0.09 0.14 0.05 0.00 0.01 0.01 0.00 0.00 | S-Steel | 14.07 14.04 14.05 14.03 14.02 14.03 14.03 14.03 14.03 14.03 | 3 3 3 3 3 3 3 3 3 3 | 0.01 0.02 0.01 0.01 0.01 0.00 0.01 0.00 0.01 0.01 -------------------------------------------------------------------------------- . anova distance type model type* model if group==42 Number of obs = 90 R-squared = 0.9903 Root MSE = .046811 Adj R-squared = 0.9856 Source | Partial SS df MS F Prob > F -----------+---------------------------------------------------- Model | 13.4156254 29 .462607771 211.11 0.0000 | type | 12.9399282 2 6.46996408 2952.61 0.0000 model | .185396713 9 .020599635 9.40 0.0000 type*model | .29030049 18 .016127805 7.36 0.0000 | Residual | .131475971 60 .002191266 -----------+---------------------------------------------------- Total | 13.5471013 89 .152214622 . table type model if group==42, c(mean distance n distance sd distance) format(%7.2f) -------------------------------------------------------------------------------- | model typelbl | 1 2 3 4 5 6 7 8 9 10 ----------+--------------------------------------------------------------------- Impregum | 31.29 31.33 31.19 31.18 31.23 31.21 31.19 31.23 31.21 31.23 | 3 3 3 3 3 3 3 3 3 3 | 0.01 0.01 0.02 0.06 0.02 0.01 0.02 0.01 0.03 0.01 | Plaster | 31.25 31.08 31.07 31.16 31.00 31.00 30.96 31.29 31.07 30.90 | 3 3 3 3 3 3 3 3 3 3 | 0.01 0.12 0.07 0.11 0.04 0.02 0.12 0.07 0.07 0.03 | S-Steel | 30.37 30.34 30.37 30.36 30.35 30.35 30.36 30.37 30.36 30.36 | 3 3 3 3 3 3 3 3 3 3 | 0.01 0.02 0.03 0.01 0.02 0.01 0.02 0.00 0.01 0.01 -------------------------------------------------------------------------------- 51 . anova distance type model type* model if group==43 Number of obs = 90 R-squared = 0.9851 Root MSE = .027246 Adj R-squared = 0.9779 Source | Partial SS df MS F Prob > F -----------+---------------------------------------------------- Model | 2.94475649 29 .101543327 136.79 0.0000 | type | 2.75075177 2 1.37537588 1852.74 0.0000 model | .061889896 9 .006876655 9.26 0.0000 type*model | .132114826 18 .007339713 9.89 0.0000 | Residual | .044540725 60 .000742345 -----------+---------------------------------------------------- Total | 2.98929722 89 .033587609 . table type model if group==43, c(mean distance n distance sd distance) format(%7.2f) -------------------------------------------------------------------------------- | model typelbl | 1 2 3 4 5 6 7 8 9 10 ----------+--------------------------------------------------------------------- Impregum | 40.66 40.72 40.65 40.64 40.64 40.65 40.61 40.66 40.65 40.65 | 3 3 3 3 3 3 3 3 3 3 | 0.01 0.00 0.01 0.03 0.01 0.01 0.01 0.00 0.01 0.01 | Plaster | 40.65 40.55 40.75 40.59 40.55 40.79 40.65 40.70 40.68 40.67 | 3 3 3 3 3 3 3 3 3 3 | 0.01 0.05 0.02 0.05 0.02 0.04 0.08 0.04 0.01 0.01 | S-Steel | 40.28 40.25 40.30 40.30 40.28 40.29 40.27 40.30 40.31 40.31 | 3 3 3 3 3 3 3 3 3 3 | 0.02 0.01 0.05 0.01 0.02 0.01 0.03 0.01 0.01 0.02 -------------------------------------------------------------------------------- . anova distance type model type* model if group==44 Number of obs = 90 R-squared = 0.9548 Root MSE = .015648 Adj R-squared = 0.9330 Source | Partial SS df MS F Prob > F -----------+---------------------------------------------------- Model | .310683858 29 .010713236 43.75 0.0000 | type | .263743248 2 .131871624 538.57 0.0000 model | .010595793 9 .00117731 4.81 0.0001 type*model | .036344817 18 .002019156 8.25 0.0000 | Residual | .014691357 60 .000244856 -----------+---------------------------------------------------- Total | .325375215 89 .003655901 . table type model if group==44, c(mean distance n distance sd distance) format(%7.2f) -------------------------------------------------------------------------------- | model typelbl | 1 2 3 4 5 6 7 8 9 10 ----------+--------------------------------------------------------------------- Impregum | 47.23 47.27 47.22 47.23 47.25 47.22 47.21 47.24 47.22 47.21 | 3 3 3 3 3 3 3 3 3 3 | 0.01 0.00 0.00 0.00 0.01 0.00 0.00 0.01 0.00 0.00 | Plaster | 47.14 47.09 47.10 47.10 47.08 47.15 47.08 47.14 47.05 47.06 | 3 3 3 3 3 3 3 3 3 3 | 0.02 0.01 0.01 0.01 0.01 0.01 0.00 0.01 0.01 0.00 | S-Steel | 47.13 47.12 47.16 47.17 47.15 47.16 47.17 47.16 47.17 47.16 | 3 3 3 3 3 3 3 3 3 3 | 0.02 0.01 0.05 0.01 0.04 0.01 0.05 0.00 0.00 0.00 -------------------------------------------------------------------------------- 52 . anova distance type model type* model if group==45 Number of obs = 90 R-squared = 0.9395 Root MSE = .020263 Adj R-squared = 0.9103 Source | Partial SS df MS F Prob > F -----------+---------------------------------------------------- Model | .382535143 29 .013190867 32.13 0.0000 | type | .16015753 2 .080078765 195.03 0.0000 model | .065652762 9 .007294751 17.77 0.0000 type*model | .156724851 18 .008706936 21.21 0.0000 | Residual | .024635493 60 .000410592 -----------+---------------------------------------------------- Total | .407170636 89 .004574951 . table type model if group==45, c(mean distance n distance sd distance) format(%7.2f) -------------------------------------------------------------------------------- | model typelbl | 1 2 3 4 5 6 7 8 9 10 ----------+--------------------------------------------------------------------- Impregum | 17.21 17.21 17.20 17.22 17.21 17.20 17.21 17.18 17.19 17.22 | 3 3 3 3 3 3 3 3 3 3 | 0.00 0.01 0.01 0.01 0.01 0.00 0.01 0.01 0.01 0.01 | Plaster | 17.19 17.20 17.12 17.23 17.21 17.05 17.02 17.24 17.11 16.99 | 3 3 3 3 3 3 3 3 3 3 | 0.02 0.00 0.01 0.01 0.00 0.01 0.07 0.04 0.05 0.02 | S-Steel | 17.09 17.08 17.10 17.11 17.11 17.10 17.11 17.11 17.11 17.11 | 3 3 3 3 3 3 3 3 3 3 | 0.02 0.00 0.02 0.00 0.01 0.00 0.01 0.00 0.00 0.00 -------------------------------------------------------------------------------- . anova distance type model type* model if group==46 Number of obs = 90 R-squared = 0.8669 Root MSE = .012059 Adj R-squared = 0.8025 Source | Partial SS df MS F Prob > F -----------+---------------------------------------------------- Model | .056806257 29 .001958836 13.47 0.0000 | type | .030587536 2 .015293768 105.18 0.0000 model | .008526503 9 .000947389 6.52 0.0000 type*model | .017692218 18 .000982901 6.76 0.0000 | Residual | .008724747 60 .000145412 -----------+---------------------------------------------------- Total | .065531004 89 .000736303 . table type model if group==46, c(mean distance n distance sd distance) format(%7.2f) -------------------------------------------------------------------------------- | model typelbl | 1 2 3 4 5 6 7 8 9 10 ----------+--------------------------------------------------------------------- Impregum | 30.13 30.14 30.16 30.16 30.11 30.13 30.12 30.13 30.14 30.15 | 3 3 3 3 3 3 3 3 3 3 | 0.01 0.00 0.01 0.01 0.01 0.01 0.01 0.01 0.00 0.01 | Plaster | 30.17 30.18 30.15 30.20 30.20 30.22 30.16 30.20 30.18 30.16 | 3 3 3 3 3 3 3 3 3 3 | 0.02 0.00 0.01 0.01 0.01 0.01 0.01 0.01 0.02 0.00 | S-Steel | 30.14 30.12 30.16 30.15 30.15 30.15 30.14 30.16 30.17 30.17 | 3 3 3 3 3 3 3 3 3 3 | 0.01 0.00 0.04 0.00 0.01 0.01 0.02 0.00 0.01 0.00 -------------------------------------------------------------------------------- 53 . anova distance type model type* model if group==47 Number of obs = 90 R-squared = 0.9820 Root MSE = .026877 Adj R-squared = 0.9734 Source | Partial SS df MS F Prob > F -----------+---------------------------------------------------- Model | 2.36953211 29 .081708004 113.11 0.0000 | type | 2.09572743 2 1.04786371 1450.54 0.0000 model | .103635824 9 .011515092 15.94 0.0000 type*model | .170168861 18 .009453826 13.09 0.0000 | Residual | .043343738 60 .000722396 -----------+---------------------------------------------------- Total | 2.41287585 89 .027110965 . table type model if group==47, c(mean distance n distance sd distance) format(%7.2f) -------------------------------------------------------------------------------- | model typelbl | 1 2 3 4 5 6 7 8 9 10 ----------+--------------------------------------------------------------------- Impregum | 40.42 40.41 40.30 40.32 40.33 40.33 40.32 40.31 40.31 40.32 | 3 3 3 3 3 3 3 3 3 3 | 0.01 0.01 0.00 0.03 0.01 0.03 0.00 0.04 0.01 0.03 | Plaster | 40.39 40.19 40.21 40.22 40.09 40.32 40.33 40.36 40.28 40.26 | 3 3 3 3 3 3 3 3 3 3 | 0.03 0.03 0.03 0.02 0.01 0.03 0.08 0.04 0.02 0.01 | S-Steel | 39.99 39.97 39.99 39.99 39.98 39.99 40.00 39.98 39.98 39.98 | 3 3 3 3 3 3 3 3 3 3 | 0.01 0.01 0.03 0.00 0.03 0.00 0.04 0.00 0.02 0.01 -------------------------------------------------------------------------------- . anova distance type model type* model if group==48 Number of obs = 90 R-squared = 0.9809 Root MSE = .02456 Adj R-squared = 0.9717 Source | Partial SS df MS F Prob > F -----------+---------------------------------------------------- Model | 1.85772709 29 .064059555 106.20 0.0000 | type | 1.04091444 2 .520457222 862.86 0.0000 model | .272464132 9 .030273792 50.19 0.0000 type*model | .544348516 18 .030241584 50.14 0.0000 | Residual | .03619075 60 .000603179 -----------+---------------------------------------------------- Total | 1.89391784 89 .021279976 . table type model if group==48, c(mean distance n distance sd distance) format(%7.2f) -------------------------------------------------------------------------------- | model typelbl | 1 2 3 4 5 6 7 8 9 10 ----------+--------------------------------------------------------------------- Impregum | 16.54 16.54 16.56 16.58 16.52 16.53 16.53 16.56 16.56 16.54 | 3 3 3 3 3 3 3 3 3 3 | 0.01 0.01 0.01 0.01 0.00 0.01 0.00 0.00 0.00 0.01 | Plaster | 16.63 16.60 16.25 16.57 16.61 16.23 16.29 16.58 16.34 16.26 | 3 3 3 3 3 3 3 3 3 3 | 0.04 0.01 0.04 0.01 0.01 0.04 0.04 0.01 0.09 0.03 | S-Steel | 16.71 16.70 16.71 16.69 16.69 16.70 16.68 16.69 16.71 16.69 | 3 3 3 3 3 3 3 3 3 3 | 0.00 0.01 0.02 0.00 0.01 0.01 0.02 0.01 0.01 0.01 -------------------------------------------------------------------------------- 54 . anova distance type model type* model if group==49 Number of obs = 90 R-squared = 0.9846 Root MSE = .04232 Adj R-squared = 0.9772 Source | Partial SS df MS F Prob > F -----------+---------------------------------------------------- Model | 6.8733753 29 .237012942 132.33 0.0000 | type | 5.5081407 2 2.75407035 1537.72 0.0000 model | .651615976 9 .072401775 40.43 0.0000 type*model | .713618633 18 .03964548 22.14 0.0000 | Residual | .107460864 60 .001791014 -----------+---------------------------------------------------- Total | 6.98083617 89 .078436361 . table type model if group==49, c(mean distance n distance sd distance) format(%7.2f) -------------------------------------------------------------------------------- | model typelbl | 1 2 3 4 5 6 7 8 9 10 ----------+--------------------------------------------------------------------- Impregum | 30.27 30.25 30.03 30.10 30.09 30.11 30.07 30.09 30.08 30.08 | 3 3 3 3 3 3 3 3 3 3 | 0.01 0.01 0.02 0.06 0.02 0.06 0.02 0.08 0.01 0.04 | Plaster | 30.31 29.83 29.79 29.83 29.67 29.72 29.84 30.20 29.85 29.72 | 3 3 3 3 3 3 3 3 3 3 | 0.08 0.04 0.05 0.04 0.02 0.06 0.04 0.01 0.12 0.04 | S-Steel | 29.55 29.53 29.53 29.51 29.51 29.52 29.51 29.50 29.50 29.49 | 3 3 3 3 3 3 3 3 3 3 | 0.01 0.01 0.02 0.01 0.02 0.02 0.02 0.02 0.03 0.03 -------------------------------------------------------------------------------- . anova distance type model type* model if group==50 Number of obs = 90 R-squared = 0.9961 Root MSE = .03498 Adj R-squared = 0.9942 Source | Partial SS df MS F Prob > F -----------+---------------------------------------------------- Model | 18.5597263 29 .639990561 523.04 0.0000 | type | 16.1627583 2 8.08137914 6604.55 0.0000 model | .717910126 9 .079767792 65.19 0.0000 type*model | 1.67905788 18 .093280993 76.23 0.0000 | Residual | .073416491 60 .001223608 -----------+---------------------------------------------------- Total | 18.6331428 89 .209361155 . table type model if group==50, c(mean distance n distance sd distance) format(%7.2f) -------------------------------------------------------------------------------- | model typelbl | 1 2 3 4 5 6 7 8 9 10 ----------+--------------------------------------------------------------------- Impregum | 14.59 14.58 14.28 14.33 14.39 14.42 14.36 14.35 14.34 14.36 | 3 3 3 3 3 3 3 3 3 3 | 0.01 0.01 0.02 0.07 0.03 0.08 0.03 0.09 0.01 0.05 | Plaster | 14.56 14.01 14.55 14.04 13.82 14.53 14.54 14.50 14.48 14.46 | 3 3 3 3 3 3 3 3 3 3 | 0.05 0.05 0.01 0.04 0.03 0.00 0.01 0.01 0.01 0.00 | S-Steel | 13.51 13.50 13.48 13.48 13.47 13.47 13.48 13.46 13.45 13.45 | 3 3 3 3 3 3 3 3 3 3 | 0.01 0.03 0.01 0.01 0.02 0.01 0.02 0.01 0.02 0.01 -------------------------------------------------------------------------------- . log off log: C:\Dudu\Von Berg\Data2m23.log log type: text 55 Comparison of the means log: C:\Dudu\Von Berg\Data2m23.log log type: text resumed on: 22 Mar 2006, 07:53:15 . oneway distance type if group==41,tabulate scheffe | Summary of distance typelbl | Mean Std. Dev. Freq. ------------+------------------------------------ Impregum | 15.04 0.06 30 Plaster | 15.03 0.12 30 S-Steel | 14.03 0.02 30 ------------+------------------------------------ Total | 14.70 0.48 90 Analysis of Variance Source SS df MS F Prob > F ------------------------------------------------------------------------ Between groups 20.104063 2 10.0520315 1517.52 0.0000 Within groups .576285145 87 .006623967 ------------------------------------------------------------------------ Total 20.6803482 89 .232363463 Bartlett's test for equal variances: chi2(2) = 81.8621 Prob>chi2 = 0.000 Comparison of distance by typelbl (Scheffe) Row Mean-| Col Mean | Impregum Plaster ---------+---------------------- Plaster | -0.01 | 0.782 | S-Steel | -1.01 -1.00 | 0.000 0.000 . oneway distance type if group==42,tabulate scheffe | Summary of distance typelbl | Mean Std. Dev. Freq. ------------+------------------------------------ Impregum | 31.23 0.05 30 Plaster | 31.08 0.14 30 S-Steel | 30.36 0.01 30 ------------+------------------------------------ Total | 30.89 0.39 90 Analysis of Variance Source SS df MS F Prob > F ------------------------------------------------------------------------ Between groups 12.9399282 2 6.46996408 927.06 0.0000 Within groups .607173174 87 .006979002 ------------------------------------------------------------------------ Total 13.5471013 89 .152214622 Bartlett's test for equal variances: chi2(2) = 101.1718 Prob>chi2 = 0.000 Comparison of distance by typelbl (Scheffe) Row Mean-| Col Mean | Impregum Plaster ---------+---------------------- Plaster | -0.15 | 0.000 | S-Steel | -0.87 -0.72 | 0.000 0.000 56 . oneway distance type if group==43,tabulate scheffe | Summary of distance typelbl | Mean Std. Dev. Freq. ------------+------------------------------------ Impregum | 40.66 0.03 30 Plaster | 40.66 0.08 30 S-Steel | 40.29 0.03 30 ------------+------------------------------------ Total | 40.53 0.18 90 Analysis of Variance Source SS df MS F Prob > F ------------------------------------------------------------------------ Between groups 2.75075177 2 1.37537588 501.61 0.0000 Within groups .238545447 87 .002741902 ------------------------------------------------------------------------ Total 2.98929722 89 .033587609 Bartlett's test for equal variances: chi2(2) = 49.1541 Prob>chi2 = 0.000 Comparison of distance by typelbl (Scheffe) Row Mean-| Col Mean | Impregum Plaster ---------+---------------------- Plaster | 0.00 | 0.972 | S-Steel | -0.37 -0.37 | 0.000 0.000 . oneway distance type if group==44,tabulate scheffe | Summary of distance typelbl | Mean Std. Dev. Freq. ------------+------------------------------------ Impregum | 47.23 0.02 30 Plaster | 47.10 0.03 30 S-Steel | 47.15 0.03 30 ------------+------------------------------------ Total | 47.16 0.06 90 Analysis of Variance Source SS df MS F Prob > F ------------------------------------------------------------------------ Between groups .263743248 2 .131871624 186.15 0.0000 Within groups .061631967 87 .000708413 ------------------------------------------------------------------------ Total .325375215 89 .003655901 Bartlett's test for equal variances: chi2(2) = 10.2315 Prob>chi2 = 0.006 Comparison of distance by typelbl (Scheffe) Row Mean-| Col Mean | Impregum Plaster ---------+---------------------- Plaster | -0.13 | 0.000 | S-Steel | -0.08 0.05 | 0.000 0.000 57 . oneway distance type if group==45,tabulate scheffe | Summary of distance typelbl | Mean Std. Dev. Freq. ------------+------------------------------------ Impregum | 17.21 0.01 30 Plaster | 17.14 0.09 30 S-Steel | 17.10 0.01 30 ------------+------------------------------------ Total | 17.15 0.07 90 Analysis of Variance Source SS df MS F Prob > F ------------------------------------------------------------------------ Between groups .16015753 2 .080078765 28.20 0.0000 Within groups .247013106 87 .002839231 ------------------------------------------------------------------------ Total .407170636 89 .004574951 Bartlett's test for equal variances: chi2(2) = 136.3753 Prob>chi2 = 0.000 Comparison of distance by typelbl (Scheffe) Row Mean-| Col Mean | Impregum Plaster ---------+---------------------- Plaster | -0.07 | 0.000 | S-Steel | -0.10 -0.03 | 0.000 0.068 . oneway distance type if group==46,tabulate scheffe | Summary of distance typelbl | Mean Std. Dev. Freq. ------------+------------------------------------ Impregum | 30.14 0.02 30 Plaster | 30.18 0.02 30 S-Steel | 30.15 0.02 30 ------------+------------------------------------ Total | 30.16 0.03 90 Analysis of Variance Source SS df MS F Prob > F ------------------------------------------------------------------------ Between groups .030587536 2 .015293768 38.08 0.0000 Within groups .034943468 87 .000401649 ------------------------------------------------------------------------ Total .065531004 89 .000736303 Bartlett's test for equal variances: chi2(2) = 5.6806 Prob>chi2 = 0.058 Comparison of distance by typelbl (Scheffe) Row Mean-| Col Mean | Impregum Plaster ---------+---------------------- Plaster | 0.04 | 0.000 | S-Steel | 0.01 -0.03 | 0.023 0.000 58 . oneway distance type if group==47,tabulate scheffe | Summary of distance typelbl | Mean Std. Dev. Freq. ------------+------------------------------------ Impregum | 40.34 0.05 30 Plaster | 40.26 0.09 30 S-Steel | 39.98 0.02 30 ------------+------------------------------------ Total | 40.20 0.16 90 Analysis of Variance Source SS df MS F Prob > F ------------------------------------------------------------------------ Between groups 2.09572743 2 1.04786371 287.45 0.0000 Within groups .317148423 87 .003645384 ------------------------------------------------------------------------ Total 2.41287585 89 .027110965 Bartlett's test for equal variances: chi2(2) = 58.5537 Prob>chi2 = 0.000 Comparison of distance by typelbl (Scheffe) Row Mean-| Col Mean | Impregum Plaster ---------+---------------------- Plaster | -0.07 | 0.000 | S-Steel | -0.35 -0.28 | 0.000 0.000 . oneway distance type if group==48,tabulate scheffe | Summary of distance typelbl | Mean Std. Dev. Freq. ------------+------------------------------------ Impregum | 16.55 0.02 30 Plaster | 16.43 0.17 30 S-Steel | 16.70 0.01 30 ------------+------------------------------------ Total | 16.56 0.15 90 Analysis of Variance Source SS df MS F Prob > F ------------------------------------------------------------------------ Between groups 1.04091444 2 .520457222 53.08 0.0000 Within groups .853003399 87 .009804637 ------------------------------------------------------------------------ Total 1.89391784 89 .021279976 Bartlett's test for equal variances: chi2(2) = 168.2924 Prob>chi2 = 0.000 Comparison of distance by typelbl (Scheffe) Row Mean-| Col Mean | Impregum Plaster ---------+---------------------- Plaster | -0.11 | 0.000 | S-Steel | 0.15 0.26 | 0.000 0.000 59 . oneway distance type if group==49,tabulate scheffe | Summary of distance typelbl | Mean Std. Dev. Freq. ------------+------------------------------------ Impregum | 30.12 0.08 30 Plaster | 29.88 0.21 30 S-Steel | 29.51 0.03 30 ------------+------------------------------------ Total | 29.84 0.28 90 Analysis of Variance Source SS df MS F Prob > F ------------------------------------------------------------------------ Between groups 5.5081407 2 2.75407035 162.70 0.0000 Within groups 1.47269547 87 .016927534 ------------------------------------------------------------------------ Total 6.98083617 89 .078436361 Bartlett's test for equal variances: chi2(2) = 92.3283 Prob>chi2 = 0.000 Comparison of distance by typelbl (Scheffe) Row Mean-| Col Mean | Impregum Plaster ---------+---------------------- Plaster | -0.24 | 0.000 | S-Steel | -0.60 -0.36 | 0.000 0.000 . oneway distance type if group==50,tabulate scheffe | Summary of distance typelbl | Mean Std. Dev. Freq. ------------+------------------------------------ Impregum | 14.40 0.11 30 Plaster | 14.35 0.27 30 S-Steel | 13.47 0.02 30 ------------+------------------------------------ Total | 14.07 0.46 90 Analysis of Variance Source SS df MS F Prob > F ------------------------------------------------------------------------ Between groups 16.1627583 2 8.08137914 284.60 0.0000 Within groups 2.4703845 87 .028395224 ------------------------------------------------------------------------ Total 18.6331428 89 .209361155 Bartlett's test for equal variances: chi2(2) = 109.0900 Prob>chi2 = 0.000 Comparison of distance by typelbl (Scheffe) Row Mean-| Col Mean | Impregum Plaster ---------+---------------------- Plaster | -0.05 | 0.492 | S-Steel | -0.92 -0.87 | 0.000 0.000 . log off log: C:\Dudu\Von Berg\Data2m23.log log type: text paused on: 22 Mar 2006, 07:54:36 60 9. APPENDIX B CAST DATA ANALYSIS OF VARIANCE AND TABLE OF MEANS log: C:\Dudu\Von Berg\Casts output.log log type: text opened on: 28 Apr 2006, 09:18:37 . anova distance type model if group==41 Number of obs = 90 R-squared = 0.9170 Root MSE = .154756 Adj R-squared = 0.9053 Source | Partial SS df MS F Prob > F -----------+---------------------------------------------------- Model | 20.6326876 11 1.87569887 78.32 0.0000 | type | 20.0656184 2 10.0328092 418.92 0.0000 model | .567069167 9 .063007685 2.63 0.0103 | Residual | 1.86805093 78 .023949371 -----------+---------------------------------------------------- Total | 22.5007385 89 .252817287 . table type model if group==41, c(mean distance sd distance n distance) col row f(%7.2f) --------------------------------------------------------------------------------------- | model type | 1 2 3 4 5 6 7 8 9 10 Total ----------+---------------------------------------------------------------------------- Plaster | 14.84 14.75 15.16 15.19 15.15 14.58 14.53 14.53 14.72 15.15 14.86 | 0.05 0.06 0.01 0.00 0.00 0.01 0.03 0.03 0.07 0.02 0.27 | 3 3 3 3 3 3 3 3 3 3 30 | Impregum | 15.19 15.20 15.18 15.17 15.16 15.20 15.19 15.19 15.17 14.84 15.15 | 0.01 0.01 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.11 | 3 3 3 3 3 3 3 3 3 3 30 | S-Steel | 14.07 14.04 14.05 14.03 14.02 14.03 14.03 14.03 14.03 14.03 14.03 | 0.01 0.02 0.01 0.01 0.01 0.00 0.01 0.00 0.01 0.01 0.02 | 3 3 3 3 3 3 3 3 3 3 30 | Total | 14.70 14.66 14.80 14.80 14.78 14.60 14.59 14.58 14.64 14.67 14.68 | 0.50 0.51 0.56 0.58 0.57 0.51 0.50 0.50 0.50 0.50 0.50 | 9 9 9 9 9 9 9 9 9 9 90 --------------------------------------------------------------------------------------- . anova distance type model if group==42 Number of obs = 90 R-squared = 0.9772 Root MSE = .065483 Adj R-squared = 0.9740 Source | Partial SS df MS F Prob > F -----------+---------------------------------------------------- Model | 14.3542234 11 1.3049294 304.32 0.0000 | type | 14.2066691 2 7.10333454 1656.53 0.0000 model | .147554322 9 .016394925 3.82 0.0005 | Residual | .334470244 78 .00428808 -----------+---------------------------------------------------- Total | 14.6886937 89 .165041502 . table type model if group==42, c(mean distance sd distance n distance) col row f(%7.2f) --------------------------------------------------------------------------------------- | model 61 type | 1 2 3 4 5 6 7 8 9 10 Total ----------+---------------------------------------------------------------------------- Plaster | 30.99 30.93 30.98 30.97 30.86 30.82 30.78 30.79 30.94 31.21 30.93 | 0.04 0.05 0.03 0.02 0.01 0.01 0.02 0.02 0.06 0.02 0.13 | 3 3 3 3 3 3 3 3 3 3 30 | Impregum | 31.30 31.34 31.30 31.33 31.32 31.34 31.36 31.32 31.32 31.34 31.33 | 0.01 0.00 0.01 0.00 0.01 0.00 0.00 0.01 0.01 0.01 0.02 | 3 3 3 3 3 3 3 3 3 3 30 | S-Steel | 30.37 30.34 30.37 30.36 30.35 30.35 30.36 30.37 30.36 30.36 30.36 | 0.01 0.02 0.03 0.01 0.02 0.01 0.02 0.00 0.01 0.01 0.01 | 3 3 3 3 3 3 3 3 3 3 30 | Total | 30.89 30.87 30.89 30.89 30.84 30.84 30.83 30.83 30.87 30.97 30.87 | 0.41 0.44 0.41 0.43 0.42 0.43 0.43 0.41 0.42 0.46 0.41 | 9 9 9 9 9 9 9 9 9 9 90 --------------------------------------------------------------------------------------- . anova distance type model if group==43 Number of obs = 90 R-squared = 0.8701 Root MSE = .072848 Adj R-squared = 0.8518 Source | Partial SS df MS F Prob > F -----------+---------------------------------------------------- Model | 2.77257971 11 .252052701 47.50 0.0000 | type | 2.57531727 2 1.28765863 242.64 0.0000 model | .197262444 9 .021918049 4.13 0.0002 | Residual | .413930289 78 .005306799 -----------+---------------------------------------------------- Total | 3.18651 89 .035803483 . table type model if group==43, c(mean distance sd distance n distance) col row f(%7.2f) --------------------------------------------------------------------------------------- | model type | 1 2 3 4 5 6 7 8 9 10 Total ----------+---------------------------------------------------------------------------- Plaster | 40.51 40.52 40.80 40.77 40.73 40.47 40.38 40.46 40.51 40.62 40.58 | 0.01 0.03 0.02 0.03 0.01 0.01 0.01 0.01 0.02 0.00 0.14 | 3 3 3 3 3 3 3 3 3 3 30 | Impregum | 40.65 40.72 40.66 40.68 40.68 40.71 40.68 40.71 40.69 40.69 40.69 | 0.00 0.00 0.01 0.00 0.01 0.00 0.00 0.01 0.00 0.01 0.02 | 3 3 3 3 3 3 3 3 3 3 30 | S-Steel | 40.28 40.25 40.30 40.30 40.28 40.29 40.27 40.30 40.31 40.31 40.29 | 0.02 0.01 0.05 0.01 0.02 0.01 0.03 0.01 0.01 0.02 0.03 | 3 3 3 3 3 3 3 3 3 3 30 | Total | 40.48 40.50 40.59 40.58 40.57 40.49 40.44 40.49 40.50 40.54 40.52 | 0.16 0.21 0.23 0.22 0.22 0.18 0.18 0.18 0.17 0.18 0.19 | 9 9 9 9 9 9 9 9 9 9 90 --------------------------------------------------------------------------------------- . anova distance type model if group==44 Number of obs = 90 R-squared = 0.5611 Root MSE = .135611 Adj R-squared = 0.4992 62 Source | Partial SS df MS F Prob > F -----------+---------------------------------------------------- Model | 1.83406097 11 .166732815 9.07 0.0000 | type | 1.21725869 2 .608629344 33.10 0.0000 model | .616802278 9 .068533586 3.73 0.0006 | Residual | 1.43444042 78 .018390262 -----------+---------------------------------------------------- Total | 3.26850139 89 .036724735 . table type model if group==44, c(mean distance sd distance n distance) col row f(%7.2f) --------------------------------------------------------------------------------------- | model type | 1 2 3 4 5 6 7 8 9 10 Total ----------+---------------------------------------------------------------------------- Plaster | 47.13 47.13 47.21 47.22 47.12 47.17 47.09 47.16 47.15 47.12 47.15 | 0.01 0.00 0.01 0.00 0.00 0.00 0.00 0.01 0.00 0.01 0.04 | 3 3 3 3 3 3 3 3 3 3 30 | Impregum | 47.24 47.99 47.25 47.27 47.29 47.29 47.28 47.29 47.83 47.28 47.40 | 0.00 0.00 0.01 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.26 | 3 3 3 3 3 3 3 3 3 3 30 | S-Steel | 47.13 47.12 47.16 47.17 47.15 47.16 47.17 47.16 47.17 47.16 47.15 | 0.02 0.01 0.05 0.01 0.04 0.01 0.05 0.00 0.00 0.00 0.03 | 3 3 3 3 3 3 3 3 3 3 30 | Total | 47.17 47.41 47.20 47.22 47.19 47.21 47.18 47.20 47.38 47.19 47.23 | 0.06 0.43 0.04 0.04 0.08 0.06 0.08 0.06 0.33 0.07 0.19 | 9 9 9 9 9 9 9 9 9 9 90 --------------------------------------------------------------------------------------- . anova distance type model if group==45 Number of obs = 90 R-squared = 0.4835 Root MSE = .098545 Adj R-squared = 0.4106 Source | Partial SS df MS F Prob > F -----------+---------------------------------------------------- Model | .708999156 11 .064454469 6.64 0.0000 | type | .267121422 2 .133560711 13.75 0.0000 model | .441877733 9 .049097526 5.06 0.0000 | Residual | .757473467 78 .009711198 -----------+---------------------------------------------------- Total | 1.46647262 89 .01647722 . table type model if group==45, c(mean distance sd distance n distance) col row f(%7.2f) --------------------------------------------------------------------------------------- | model type | 1 2 3 4 5 6 7 8 9 10 Total ----------+---------------------------------------------------------------------------- Plaster | 17.11 17.11 16.97 16.93 16.89 17.15 17.18 17.16 17.19 17.11 17.08 | 0.01 0.01 0.01 0.01 0.01 0.00 0.01 0.00 0.00 0.00 0.11 | 3 3 3 3 3 3 3 3 3 3 30 | Impregum | 17.11 17.13 17.13 17.17 17.16 17.16 17.18 17.14 17.16 17.71 17.21 | 0.01 0.00 0.01 0.00 0.01 0.01 0.00 0.00 0.01 0.00 0.17 | 3 3 3 3 3 3 3 3 3 3 30 | S-Steel | 17.09 17.08 17.10 17.11 17.11 17.10 17.11 17.11 17.11 17.11 17.10 | 0.02 0.00 0.02 0.00 0.01 0.00 0.01 0.00 0.00 0.00 0.01 | 3 3 3 3 3 3 3 3 3 3 30 | Total | 17.11 17.11 17.07 17.07 17.06 17.14 17.16 17.14 17.15 17.31 17.13 | 0.02 0.02 0.08 0.11 0.13 0.03 0.03 0.02 0.04 0.30 0.13 | 9 9 9 9 9 9 9 9 9 9 90 --------------------------------------------------------------------------------------- . anova distance type model if group==46 Number of obs = 90 R-squared = 0.3329 63 Root MSE = .091087 Adj R-squared = 0.2389 Source | Partial SS df MS F Prob > F -----------+---------------------------------------------------- Model | .323017089 11 .02936519 3.54 0.0005 | type | .011156822 2 .005578411 0.67 0.5134 model | .311860267 9 .034651141 4.18 0.0002 | Residual | .647156067 78 .008296873 -----------+---------------------------------------------------- Total | .970173156 89 .010900822 . table type model if group==46, c(mean distance sd distance n distance) col row f(%7.2f) --------------------------------------------------------------------------------------- | model type | 1 2 3 4 5 6 7 8 9 10 Total ----------+---------------------------------------------------------------------------- Plaster | 30.09 30.11 30.19 30.14 30.16 30.16 30.12 30.15 30.19 30.11 30.14 | 0.00 0.01 0.01 0.01 0.00 0.00 0.01 0.00 0.01 0.00 0.03 | 3 3 3 3 3 3 3 3 3 3 30 | Impregum | 30.02 30.05 30.05 30.09 30.08 30.07 30.06 30.08 30.08 30.65 30.12 | 0.01 0.01 0.01 0.00 0.00 0.00 0.01 0.01 0.01 0.00 0.18 | 3 3 3 3 3 3 3 3 3 3 30 | S-Steel | 30.14 30.12 30.16 30.15 30.15 30.15 30.14 30.16 30.17 30.17 30.15 | 0.01 0.00 0.04 0.00 0.01 0.01 0.02 0.00 0.01 0.00 0.02 | 3 3 3 3 3 3 3 3 3 3 30 | Total | 30.08 30.10 30.13 30.13 30.13 30.13 30.11 30.13 30.15 30.31 30.14 | 0.05 0.03 0.06 0.03 0.04 0.04 0.04 0.04 0.05 0.25 0.10 | 9 9 9 9 9 9 9 9 9 9 90 --------------------------------------------------------------------------------------- . anova distance type model if group==47 Number of obs = 90 R-squared = 0.7625 Root MSE = .148426 Adj R-squared = 0.7291 Source | Partial SS df MS F Prob > F -----------+---------------------------------------------------- Model | 5.51804239 11 .501640217 22.77 0.0000 | type | 4.67168096 2 2.33584048 106.03 0.0000 model | .846361433 9 .094040159 4.27 0.0002 | Residual | 1.71835193 78 .022030153 -----------+---------------------------------------------------- Total | 7.23639432 89 .081307801 . table type model if group==47, c(mean distance sd distance n distance) col row f(%7.2f) --------------------------------------------------------------------------------------- | model type | 1 2 3 4 5 6 7 8 9 10 Total ----------+---------------------------------------------------------------------------- Plaster | 40.17 40.08 40.31 40.31 40.25 40.07 40.06 40.04 40.20 40.31 40.18 | 0.03 0.01 0.00 0.02 0.01 0.01 0.01 0.01 0.04 0.01 0.11 | 3 3 3 3 3 3 3 3 3 3 30 | Impregum | 40.33 41.03 40.34 40.37 40.38 40.35 40.36 40.37 40.92 40.88 40.53 | 0.01 0.01 0.00 0.01 0.01 0.00 0.00 0.00 0.00 0.01 0.28 | 3 3 3 3 3 3 3 3 3 3 30 | S-Steel | 39.99 39.97 39.99 39.99 39.98 39.99 40.00 39.98 39.98 39.98 39.98 | 0.01 0.01 0.03 0.00 0.03 0.00 0.04 0.00 0.02 0.01 0.02 | 3 3 3 3 3 3 3 3 3 3 30 | Total | 40.16 40.36 40.21 40.22 40.20 40.14 40.14 40.13 40.37 40.39 40.23 | 0.15 0.51 0.17 0.18 0.18 0.17 0.17 0.18 0.42 0.40 0.29 | 9 9 9 9 9 9 9 9 9 9 90 --------------------------------------------------------------------------------------- 64 . anova distance type model if group==48 Number of obs = 90 R-squared = 0.5501 Root MSE = .081434 Adj R-squared = 0.4867 Source | Partial SS df MS F Prob > F -----------+---------------------------------------------------- Model | .632477278 11 .057497934 8.67 0.0000 | type | .390016289 2 .195008144 29.41 0.0000 model | .242460989 9 .02694011 4.06 0.0003 | Residual | .517253711 78 .006631458 -----------+---------------------------------------------------- Total | 1.14973099 89 .012918326 . table type model if group==48, c(mean distance sd distance n distance) col row f(%7.2f) --------------------------------------------------------------------------------------- | model type | 1 2 3 4 5 6 7 8 9 10 Total ----------+---------------------------------------------------------------------------- Plaster | 16.64 16.66 16.33 16.32 16.26 16.66 16.59 16.64 16.65 16.63 16.54 | 0.00 0.00 0.02 0.05 0.01 0.00 0.00 0.00 0.01 0.01 0.16 | 3 3 3 3 3 3 3 3 3 3 30 | Impregum | 16.60 16.60 16.60 16.61 16.59 16.58 16.57 16.61 16.60 16.55 16.59 | 0.01 0.01 0.00 0.00 0.02 0.00 0.01 0.01 0.00 0.01 0.02 | 3 3 3 3 3 3 3 3 3 3 30 | S-Steel | 16.71 16.70 16.71 16.69 16.69 16.70 16.68 16.69 16.71 16.69 16.70 | 0.00 0.01 0.02 0.00 0.01 0.01 0.02 0.01 0.01 0.01 0.01 | 3 3 3 3 3 3 3 3 3 3 30 | Total | 16.65 16.66 16.55 16.54 16.51 16.65 16.61 16.65 16.65 16.62 16.61 | 0.04 0.04 0.17 0.17 0.20 0.05 0.05 0.03 0.05 0.06 0.11 | 9 9 9 9 9 9 9 9 9 9 90 --------------------------------------------------------------------------------------- . anova distance type model if group==49 Number of obs = 90 R-squared = 0.8850 Root MSE = .148125 Adj R-squared = 0.8688 Source | Partial SS df MS F Prob > F -----------+---------------------------------------------------- Model | 13.167992 11 1.19709018 54.56 0.0000 | type | 12.285059 2 6.14252948 279.96 0.0000 model | .882933067 9 .098103674 4.47 0.0001 | Residual | 1.7113886 78 .021940879 -----------+---------------------------------------------------- Total | 14.8793806 89 .167184052 . table type model if group==49, c(mean distance sd distance n distance) col row f(%7.2f) --------------------------------------------------------------------------------------- | model type | 1 2 3 4 5 6 7 8 9 10 Total ----------+---------------------------------------------------------------------------- Plaster | 29.96 29.80 29.81 29.81 29.65 29.64 29.61 29.58 29.83 30.21 29.79 | 0.07 0.02 0.03 0.07 0.03 0.02 0.02 0.02 0.09 0.01 0.19 | 3 3 3 3 3 3 3 3 3 3 30 | Impregum | 30.31 30.92 30.29 30.30 30.30 30.27 30.27 30.31 30.77 30.24 30.40 | 0.01 0.01 0.00 0.01 0.02 0.00 0.00 0.01 0.00 0.00 0.23 | 3 3 3 3 3 3 3 3 3 3 30 | S-Steel | 29.55 29.53 29.53 29.51 29.51 29.52 29.51 29.50 29.50 29.49 29.51 | 0.01 0.01 0.02 0.01 0.02 0.02 0.02 0.02 0.03 0.03 0.03 | 3 3 3 3 3 3 3 3 3 3 30 | Total | 29.94 30.09 29.88 29.88 29.82 29.81 29.80 29.79 30.03 29.98 29.90 | 0.33 0.64 0.33 0.35 0.37 0.35 0.36 0.39 0.57 0.37 0.41 | 9 9 9 9 9 9 9 9 9 9 90 --------------------------------------------------------------------------------------- 65 . anova distance type model if group==50 Number of obs = 90 R-squared = 0.8607 Root MSE = .208728 Adj R-squared = 0.8410 Source | Partial SS df MS F Prob > F -----------+---------------------------------------------------- Model | 20.9891267 11 1.90810242 43.80 0.0000 | type | 19.7671652 2 9.88358258 226.86 0.0000 model | 1.22196151 9 .135773501 3.12 0.0030 | Residual | 3.39825596 78 .043567384 -----------+---------------------------------------------------- Total | 24.3873826 89 .274015535 . table type model if group==50, c(mean distance sd distance n distance) col row f(%7.2f) --------------------------------------------------------------------------------------- | model type | 1 2 3 4 5 6 7 8 9 10 Total ----------+---------------------------------------------------------------------------- Plaster | 14.07 13.88 14.48 14.48 14.42 13.66 13.71 13.63 13.92 14.43 14.07 | 0.09 0.02 0.00 0.01 0.01 0.03 0.02 0.02 0.13 0.01 0.35 | 3 3 3 3 3 3 3 3 3 3 30 | Impregum | 14.53 15.08 14.52 14.52 14.54 14.52 14.52 14.53 14.94 14.52 14.62 | 0.01 0.01 0.00 0.00 0.01 0.00 0.01 0.00 0.00 0.00 0.20 | 3 3 3 3 3 3 3 3 3 3 30 | S-Steel | 13.51 13.50 13.48 13.48 13.47 13.47 13.48 13.46 13.45 13.45 13.47 | 0.01 0.03 0.01 0.01 0.02 0.01 0.02 0.01 0.02 0.01 0.02 | 3 3 3 3 3 3 3 3 3 3 30 | Total | 14.04 14.15 14.16 14.16 14.15 13.88 13.90 13.87 14.10 14.13 14.06 | 0.45 0.71 0.51 0.51 0.51 0.48 0.47 0.50 0.66 0.51 0.52 | 9 9 9 9 9 9 9 9 9 9 90 --------------------------------------------------------------------------------------- 66 COMPARISON OF THE TYPES . oneway distance type if group==41,tabulate scheffe | Summary of distance type | Mean Std. Dev. Freq. ------------+------------------------------------ Plaster | 14.860633 .26884177 30 Impregum | 15.149033 .10691004 30 S-Steel | 14.034833 .01624825 30 ------------+------------------------------------ Total | 14.6815 .50280939 90 Analysis of Variance Source SS df MS F Prob > F ------------------------------------------------------------------------ Between groups 20.0656184 2 10.0328092 358.44 0.0000 Within groups 2.4351201 87 .027989886 ------------------------------------------------------------------------ Total 22.5007385 89 .252817287 Bartlett's test for equal variances: chi2(2) = 131.6893 Prob>chi2 = 0.000 Comparison of distance by type (Scheffe) Row Mean-| Col Mean | Plaster Impregum ---------+---------------------- Impregum | .2884 | 0.000 | S-Steel | -.8258 -1.1142 | 0.000 0.000 . oneway distance type if group==42,tabulate scheffe | Summary of distance type | Mean Std. Dev. Freq. ------------+------------------------------------ Plaster | 30.9274 .12665827 30 Impregum | 31.328333 .01891238 30 S-Steel | 30.3599 .01488427 30 ------------+------------------------------------ Total | 30.871878 .406253 90 Analysis of Variance Source SS df MS F Prob > F ------------------------------------------------------------------------ Between groups 14.2066691 2 7.10333454 1282.07 0.0000 Within groups .482024567 87 .005540512 ------------------------------------------------------------------------ Total 14.6886937 89 .165041502 Bartlett's test for equal variances: chi2(2) = 139.8494 Prob>chi2 = 0.000 Comparison of distance by type (Scheffe) Row Mean-| Col Mean | Plaster Impregum ---------+---------------------- Impregum | .400933 | 0.000 | S-Steel | -.5675 -.968433 | 0.000 0.000 67 . oneway distance type if group==43,tabulate scheffe | Summary of distance type | Mean Std. Dev. Freq. ------------+------------------------------------ Plaster | 40.5775 .14124148 30 Impregum | 40.687767 .02217436 30 S-Steel | 40.286733 .02519433 30 ------------+------------------------------------ Total | 40.517333 .18921808 90 Analysis of Variance Source SS df MS F Prob > F ------------------------------------------------------------------------ Between groups 2.57531727 2 1.28765863 183.29 0.0000 Within groups .611192733 87 .007025204 ------------------------------------------------------------------------ Total 3.18651 89 .035803483 Bartlett's test for equal variances: chi2(2) = 114.8125 Prob>chi2 = 0.000 Comparison of distance by type (Scheffe) Row Mean-| Col Mean | Plaster Impregum ---------+---------------------- Impregum | .110267 | 0.000 | S-Steel | -.290767 -.401033 | 0.000 0.000 . oneway distance type if group==44,tabulate scheffe | Summary of distance type | Mean Std. Dev. Freq. ------------+------------------------------------ Plaster | 47.150533 .03985468 30 Impregum | 47.399067 .26154395 30 S-Steel | 47.154233 .02718225 30 ------------+------------------------------------ Total | 47.234611 .19163699 90 Analysis of Variance Source SS df MS F Prob > F ------------------------------------------------------------------------ Between groups 1.21725869 2 .608629344 25.81 0.0000 Within groups 2.0512427 87 .023577502 ------------------------------------------------------------------------ Total 3.26850139 89 .036724735 Bartlett's test for equal variances: chi2(2) = 145.5342 Prob>chi2 = 0.000 Comparison of distance by type (Scheffe) Row Mean-| Col Mean | Plaster Impregum ---------+---------------------- Impregum | .248533 | 0.000 | S-Steel | .0037 -.244833 | 0.996 0.000 68 . oneway distance type if group==45,tabulate scheffe | Summary of distance type | Mean Std. Dev. Freq. ------------+------------------------------------ Plaster | 17.079933 .10544289 30 Impregum | 17.205933 .17346925 30 S-Steel | 17.104867 .01213071 30 ------------+------------------------------------ Total | 17.130244 .12836363 90 Analysis of Variance Source SS df MS F Prob > F ------------------------------------------------------------------------ Between groups .267121422 2 .133560711 9.69 0.0002 Within groups 1.1993512 87 .013785646 ------------------------------------------------------------------------ Total 1.46647262 89 .01647722 Bartlett's test for equal variances: chi2(2) = 113.5159 Prob>chi2 = 0.000 Comparison of distance by type (Scheffe) Row Mean-| Col Mean | Plaster Impregum ---------+---------------------- Impregum | .126 | 0.000 | S-Steel | .024933 -.101067 | 0.714 0.005 . oneway distance type if group==46,tabulate scheffe | Summary of distance type | Mean Std. Dev. Freq. ------------+------------------------------------ Plaster | 30.142767 .03245122 30 Impregum | 30.124367 .17803728 30 S-Steel | 30.151 .0178654 30 ------------+------------------------------------ Total | 30.139378 .104407 90 Analysis of Variance Source SS df MS F Prob > F ------------------------------------------------------------------------ Between groups .011156822 2 .005578411 0.51 0.6046 Within groups .959016333 87 .011023176 ------------------------------------------------------------------------ Total .970173156 89 .010900822 Bartlett's test for equal variances: chi2(2) = 138.0721 Prob>chi2 = 0.000 Comparison of distance by type (Scheffe) Row Mean-| Col Mean | Plaster Impregum ---------+---------------------- Impregum | -.0184 | 0.795 | S-Steel | .008233 .026633 | 0.955 0.619 69 . oneway distance type if group==47,tabulate scheffe | Summary of distance type | Mean Std. Dev. Freq. ------------+------------------------------------ Plaster | 40.178867 .10848637 30 Impregum | 40.5344 .27624459 30 S-Steel | 39.9841 .01892153 30 ------------+------------------------------------ Total | 40.232456 .28514523 90 Analysis of Variance Source SS df MS F Prob > F ------------------------------------------------------------------------ Between groups 4.67168096 2 2.33584048 79.24 0.0000 Within groups 2.56471337 87 .029479464 ------------------------------------------------------------------------ Total 7.23639432 89 .081307801 Bartlett's test for equal variances: chi2(2) = 125.0434 Prob>chi2 = 0.000 Comparison of distance by type (Scheffe) Row Mean-| Col Mean | Plaster Impregum ---------+---------------------- Impregum | .355533 | 0.000 | S-Steel | -.194767 -.5503 | 0.000 0.000 . oneway distance type if group==48,tabulate scheffe | Summary of distance type | Mean Std. Dev. Freq. ------------+------------------------------------ Plaster | 16.538567 .15983713 30 Impregum | 16.591467 .02066437 30 S-Steel | 16.696933 .01490414 30 ------------+------------------------------------ Total | 16.608989 .11365881 90 Analysis of Variance Source SS df MS F Prob > F ------------------------------------------------------------------------ Between groups .390016289 2 .195008144 22.33 0.0000 Within groups .7597147 87 .008732353 ------------------------------------------------------------------------ Total 1.14973099 89 .012918326 Bartlett's test for equal variances: chi2(2) = 160.4045 Prob>chi2 = 0.000 Comparison of distance by type (Scheffe) Row Mean-| Col Mean | Plaster Impregum ---------+---------------------- Impregum | .0529 | 0.096 | S-Steel | .158367 .105467 | 0.000 0.000 70 . oneway distance type if group==49,tabulate scheffe | Summary of distance type | Mean Std. Dev. Freq. ------------+------------------------------------ Plaster | 29.789033 .18768471 30 Impregum | 30.3985 .23151491 30 S-Steel | 29.5144 .0251925 30 ------------+------------------------------------ Total | 29.900644 .40888146 90 Analysis of Variance Source SS df MS F Prob > F ------------------------------------------------------------------------ Between groups 12.285059 2 6.14252948 205.99 0.0000 Within groups 2.59432167 87 .029819789 ------------------------------------------------------------------------ Total 14.8793806 89 .167184052 Bartlett's test for equal variances: chi2(2) = 88.4537 Prob>chi2 = 0.000 Comparison of distance by type (Scheffe) Row Mean-| Col Mean | Plaster Impregum ---------+---------------------- Impregum | .609467 | 0.000 | S-Steel | -.274633 -.8841 | 0.000 0.000 . oneway distance type if group==50,tabulate scheffe | Summary of distance type | Mean Std. Dev. Freq. ------------+------------------------------------ Plaster | 14.0684 .34530552 30 Impregum | 14.622533 .19874429 30 S-Steel | 13.4748 .02413811 30 ------------+------------------------------------ Total | 14.055244 .52346493 90 Analysis of Variance Source SS df MS F Prob > F ------------------------------------------------------------------------ Between groups 19.7671652 2 9.88358258 186.11 0.0000 Within groups 4.62021747 87 .053105948 ------------------------------------------------------------------------ Total 24.3873826 89 .274015535 Bartlett's test for equal variances: chi2(2) = 114.2391 Prob>chi2 = 0.000 Comparison of distance by type (Scheffe) Row Mean-| Col Mean | Plaster Impregum ---------+---------------------- Impregum | .554133 | 0.000 | S-Steel | -.5936 -1.14773 | 0.000 0.000 . log close log: C:\Dudu\Von Berg\Casts output.log log type: text closed on: 28 Apr 2006, 09:33:43 ------------------------------------------------------------------------------------------------------- ------------------------------ 71 12. 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