A comparison of some methods of modeling baseline hazard function in discrete survival models
| dc.contributor.advisor | Bere, Alphonce | |
| dc.contributor.advisor | Sigauke, Caston | |
| dc.contributor.author | Mashabela, Mahlageng Retang | |
| dc.date | 2019 | |
| dc.date.accessioned | 2019-10-22T12:35:24Z | |
| dc.date.available | 2019-10-22T12:35:24Z | |
| dc.date.issued | 2019-09-20 | |
| dc.description | MSc (Statistics) | en_US |
| dc.description | Department of Statistics | |
| dc.description.abstract | The baseline parameter vector in a discrete-time survival model is determined by the number of time points. The larger the number of the time points, the higher the dimension of the baseline parameter vector which often leads to biased maximum likelihood estimates. One of the ways to overcome this problem is to use a simpler parametrization that contains fewer parameters. A simulation approach was used to compare the accuracy of three variants of penalised regression spline methods in smoothing the baseline hazard function. Root mean squared error (RMSE) analysis suggests that generally all the smoothing methods performed better than the model with a discrete baseline hazard function. No single smoothing method outperformed the other smoothing methods. These methods were also applied to data on age at rst alcohol intake in Thohoyandou. The results from real data application suggest that there were no signi cant di erences amongst the estimated models. Consumption of other drugs, having a parent who drinks, being a male and having been abused in life are associated with high chances of drinking alcohol very early in life. | en_US |
| dc.description.sponsorship | NRF | en_US |
| dc.format.extent | 1 online resource (xiii, 87 leaves : color illustrations) | |
| dc.identifier.apacitation | Mashabela, M. R. (2019). <i>A comparison of some methods of modeling baseline hazard function in discrete survival models</i>. (). . Retrieved from http://hdl.handle.net/11602/1498 | en_ZA |
| dc.identifier.chicagocitation | Mashabela, Mahlageng Retang. <i>"A comparison of some methods of modeling baseline hazard function in discrete survival models."</i> ., , 2019. http://hdl.handle.net/11602/1498 | en_ZA |
| dc.identifier.citation | Mashabela, Mahlageng Retang (2019) A comparison of some methods of modeling baseline hazard function in discrete survival models, University of Venda, South Africa.<http://hdl.handle.net/11602/1498>. | |
| dc.identifier.ris | TY - Dissertation AU - Mashabela, Mahlageng Retang AB - The baseline parameter vector in a discrete-time survival model is determined by the number of time points. The larger the number of the time points, the higher the dimension of the baseline parameter vector which often leads to biased maximum likelihood estimates. One of the ways to overcome this problem is to use a simpler parametrization that contains fewer parameters. A simulation approach was used to compare the accuracy of three variants of penalised regression spline methods in smoothing the baseline hazard function. Root mean squared error (RMSE) analysis suggests that generally all the smoothing methods performed better than the model with a discrete baseline hazard function. No single smoothing method outperformed the other smoothing methods. These methods were also applied to data on age at rst alcohol intake in Thohoyandou. The results from real data application suggest that there were no signi cant di erences amongst the estimated models. Consumption of other drugs, having a parent who drinks, being a male and having been abused in life are associated with high chances of drinking alcohol very early in life. DA - 2019-09-20 DB - ResearchSpace DP - Univen KW - Discrete survival models KW - Hazard function KW - Baseline hazard function KW - Smoothing splines KW - Penalised regression splines KW - RMSE LK - https://univendspace.univen.ac.za PY - 2019 T1 - A comparison of some methods of modeling baseline hazard function in discrete survival models TI - A comparison of some methods of modeling baseline hazard function in discrete survival models UR - http://hdl.handle.net/11602/1498 ER - | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/11602/1498 | |
| dc.identifier.vancouvercitation | Mashabela MR. A comparison of some methods of modeling baseline hazard function in discrete survival models. []. , 2019 [cited yyyy month dd]. Available from: http://hdl.handle.net/11602/1498 | en_ZA |
| dc.language.iso | en | en_US |
| dc.rights | University of Venda | |
| dc.subject | Discrete survival models | en_US |
| dc.subject | UCTD | en_ZA |
| dc.subject | Baseline hazard function | en_US |
| dc.subject | Smoothing splines | en_US |
| dc.subject | Penalised regression splines | en_US |
| dc.subject | RMSE | en_US |
| dc.subject.ddc | 511.442 | |
| dc.subject.lcsh | Spline theory | |
| dc.subject.lcsh | Polynominals | |
| dc.subject.lcsh | Aproximation theory | |
| dc.title | A comparison of some methods of modeling baseline hazard function in discrete survival models | en_US |
| dc.type | Dissertation | en_US |