Fixed Effects Regression Methods for Longitudinal Data Using SAS

5.7. Summary

Fixed effect regression analysis of event history data is easily accomplished when each individual has multiple, usually repeated, events. Like logistic regression, and unlike linear regression or Poisson regression, the use of dummy variables to represent the fixed effects typically leads to biased coefficient estimates for the other variables. Instead, the preferred method for fixed effects event history analysis is to do Cox regression with stratification to eliminate the fixed effects from the estimating equations. In PROC PHREG this is implemented by using the STRATA statement with a variable containing common ID numbers for each individual. This method is computationally efficient even for large numbers of strata and produces ...