seminars:stat:160317
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| seminars:stat:160317 [2016/03/07 16:40] – shang | seminars:stat:160317 [2016/05/02 01:46] (current) – aleksey | ||
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| + | we propose several new diagnostic plotting methods for the Cox models | ||
| + | with the general external time-dependent covariates $Z$, | ||
| + | which can be continuous, or with the | ||
| + | time-varying regression coefficients. | ||
| + | The main approach compares the non-parametric | ||
| + | MLE of the survival function | ||
| + | against its expected (correct) expression under the | ||
| + | given Cox model which can be mis-specified. | ||
| + | This is different from the existing methods in the literatures such as | ||
| + | log-log plots and residuals plots. | ||
| + | The simulation studies and the data analysis of our breast cancer | ||
| + | data suggest that the combination of these | ||
| + | diagnostic plotting methods we proposed performs quite satisfactorily. | ||
| + | These new diagnostic plotting methods naturally yield various | ||
| + | tests for checking the validity of the Cox models. | ||
| + | The main advantage of the new tests over the residual tests is | ||
| + | in the case that the data do not fit any PH model. | ||
| + | Then the new tests are still valid but not the residual tests. | ||
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