Hi, I
am working on fitting a proportional hazard model to predict the
probability of default for mortgage loans. I have a question regarding
survfit function. My
historical data set is a pool of loans with monthly observed default
status for the next 24 months. The data is left truncated (delayed entry
to observation window after the loan is opened) and right censored. I
would like to fit the model with time varying covariate such as
unemployment rates and time constant variables at loan application, and
then use the model to predict the probability of default in the next 24
month for the pool of loans we have right now, by using function
survfit. When loans are outside of the observed time window, is it
reliable to use survfit function to do the prediction? If itÂ’s not
reliable, how to deal with this problem? Is there another way to set the
model? Any thoughts are appreciated. Thanks so much in advance. Ying(Cindy)
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