
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 it’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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