Survival analysis of bank loans in the presence of long-term survivors
| dc.article.end-page | 216 | en_ZA |
| dc.article.start-page | 199 | en_ZA |
| dc.citation.doi | https://doi.org/10.37920/sasj.2017.51.1.11 | |
| dc.contributor.author | Marimo, M | |
| dc.contributor.author | Chimedza, C | |
| dc.date.accessioned | 2020-07-14T11:08:20Z | |
| dc.date.available | 2020-07-14T11:08:20Z | |
| dc.date.issued | 2017-04 | |
| dc.description.abstract | In this paper we model competing risks, default and early settlement events, in the presence of long term survivors and compare survival and logistic methodologies. Cause specific Cox regression models were fitted and adjustments were made to accommodate a proportion of long term survivors. Methodologies were compared using ROC curves and area under the curves. The results show that survival methods perform better than logistic regression methods when modelling lifetime data in the presence of competing risks and in the presence of long term survivors. | en_ZA |
| dc.description.librarian | TT2020 | en_ZA |
| dc.faculty | Faculty of Science | en_ZA |
| dc.identifier.citation | DHET SOUTH AFRICAN LIST (JANUARY 2017) | en_ZA |
| dc.identifier.issn | ISSN: 0038-271X | |
| dc.identifier.issn | ESSN: 1996-8450 | |
| dc.identifier.uri | https://hdl.handle.net/10539/29256 | |
| dc.journal.issue | 1 | en_ZA |
| dc.journal.link | 0038271X | en_ZA |
| dc.journal.title | South African Statistical Journal | en_ZA |
| dc.journal.volume | 51 | en_ZA |
| dc.language.iso | en | en_ZA |
| dc.publisher | South African Statistical Association | en_ZA |
| dc.school | School of Statistics and Actuarial Science | en_ZA |
| dc.subject | Cause specific | en_ZA |
| dc.subject | Competing risk | en_ZA |
| dc.subject | Consumer credit | en_ZA |
| dc.subject | Proportional hazards | en_ZA |
| dc.title | Survival analysis of bank loans in the presence of long-term survivors | en_ZA |
| dc.title.alternative | South African Statistical Journal | en_ZA |
| dc.type | Article | en_ZA |