Diagnostic plots in Cox's regression model.
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.
Chen
C H
CH
Institute of Statistical Science, Academia Sinica, Taipei, Taiwan, Republic of China.
Wang
P C
PC
D000704:Analysis of Variance; D001806:Blood Urea Nitrogen; D002118:Calcium / Q000097:blood; D003933:Diagnosis; D006454:Hemoglobins / Q000032:analysis; D006801:Humans; D008175:Lung Neoplasms / Q000188:drug therapy*; D009101:Multiple Myeloma / Q000503:physiopathology*; D011379:Prognosis; D016016:Proportional Hazards Models
D006454:Hemoglobins; D002118:Calcium