A simulation study on competing risks with censored data using cox model
A simulation study was performed to compare two regression methods for competing risks with censored data. The first method was the conventional Cox's proportional hazard regression model (Cox model). The second method was based on Cox model using a duplicated data technique of Lunn and McNe...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English English |
| Published: |
1999
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/8651/1/FSAS_1999_3_IR.pdf |
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| Summary: | A simulation study was performed to compare two regression methods
for competing risks with censored data. The first method was the conventional
Cox's proportional hazard regression model (Cox model). The second method
was based on Cox model using a duplicated data technique of Lunn and McNeil
(or the modified Lunn-McNeil). Samples with various sizes and censoring
percentages were generated and fitted using both methods. This study was
conducted by comparing the inference of both methods, using Root Mean
Square Error (RMSE), the power tests, and the Schoenfeld residuals analysis.
The power tests used in this study were likelihood ratio test, Rao-score test, and
Wald statistics. The Schoenfeld residuals analysis was conducted to check the
proportionality of the model through its covariates. The estimated parameters
were computed for cause-specific hazards. Results showed the RMSE were generally smaller for the model of the modified Lunn-McNeil method than that
of the ordinary Cox method. The power tests of the likelihood ratio statistics
and Rao-score test were only powerful for the unstratified Cox model, so that, it
could be concluded that the model had more advantages than the modified
Lunn-McNeil one. However, results from the analysis of Schoenfeld residuals
indicated that the modified Lunn-McNeil was better than the ordinary Cox in
complying with the proportional hazards model assumption with respect to
certain covariates. |
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