Regression Diagnostics of the Semiparametric Proportional Rate Model for Irregularly Spaced Repeated Measurements

Counting process techniques have been successfully introduced to semiparametric inference of repeated measurements. Cheng and Wei (2000 Cheng , S. C. , Wei , L. J. ( 2000 ). Inference for a semiparametric model with panel data . Biometrika 87 : 89 – 97 .Crossref], Web of Science ®] , Google Scholar]) proposed a simple inference procedure for the semiparametric proportional rate model, which reduces to relative risk regression models for binary data. While the baseline mean functions are completely unspecified, it still requires several assumptions for valid inference. In this article, a goodness-of-fit test for it is proposed based on cumulative residuals. Theoretical justification is provided and an illustration with a dataset from a clinical trial is given. Results of simulation studies to evaluate finite sample performance are also provided.