Cox′s proportional hazards regression model is a useful statistical tool for the analysis of 'survival data' from longitudinal studies. This multivariate method compares the 'survival experience' between two or more exposure groups while allowing for simultaneous adjustment of confounding due to one or more covariates. In addition to the summary regression statistics, further insight on the exposure-response relationship can be gained by visually examining the covariates-adjusted survival curves in the respective comparison groups. Covariates-adjusted survival curves are usually computed by the 'average covariate method'. This method is, however, subject to potential drawbacks. A method that avoids these drawbacks is to estimate adjusted survival curves by the corrected group prognostic curves approach. We have written a computer program to construct survival curves by the latter method. The program is coded in the Interactive Matrix Language of SAS.
['James Lee', 'Carl Yoshizawa', 'Lynne R. Wilkens', 'H.P. Lee']
Covariance adjustment of survival curves based on Cox's proportional hazards regression model