Cox proportional hazard model and non-randomly selected sample

Are there any methods to correct bias in Cox proportional hazard model caused by non-randomly selected sample (something like Heckman’s correction)?

Background:

Lets say the situation looks as follows:

• During first two years all clients are accepted.

• After those two years a Cox PH model is build. Model predicts how long clients will use our service.

• Due to the policy of the company from now on only clients with probability of surviving 3 month greater than 0.5 are accepted, the others are rejected.

• After another two years a new model needs to be built. The problem is that we have target only for accepted clients and using only these clients might cause some serious bias.

There are proposed solutions to parametric hazard models. Take a look at these:

Prieger, James, 2000.“A Generalized Parametric Selection Model for Non-normal Data,” Working Papers 00-9, University of California at Davis, Department of Economics.

Boehmke, Frederick J., Daniel Morey and Megan Shannon. 2006. “Selection Bias and Continuous-Time Duration Models: Consequences and a Proposed Solution.” American Journal of Political Science 50 (1): 192-207.

There is code for the later paper in Stata, package “dursel”

However, I am not aware of a solution for the semiparametric Cox model.

引用自：https://stats.stackexchange.com/questions/22961