Abstract
Two diagnostic plots are presented for validating the fitting of a Cox proportional hazards model. The added variable plot is developed to assess the effect of adding a covariate to the model. The constructed variable plot is applied to detect nonlinearity of a fitted covariate. Both plots are also useful for identifying influential observations on the issues of interest. The methods are illustrated on examples of multiple myeloma and lung cancer data.
| Original language | English |
|---|---|
| Pages (from-to) | 841-850 |
| Number of pages | 10 |
| Journal | Biometrics |
| Volume | 47 |
| Issue number | 3 |
| DOIs | |
| State | Published - 1991 |
| Externally published | Yes |
