I am conducting a survival analysis of clustered data. The goal is to identify prognostic factors for the outcome from a set of several factors of interest. The data are clustered so I am using COVS(AGGREGATE) along with the ID statement to specify the clustering variable in PROC PHREG (the observational unit is an eye and the clustering variable is mouseID -- each mouse has two eyes). To perform a backwards stepwise selection, I am using the SELECTION=STEPWISE option along with START=100 to include all candidate variables in the initial model (100 is much larger than the actual number of variables) and INCLUDE=1 to include one control variable in all models. It seems to me that PROC PHREG is using the Type 3 p-values with "Model-based Variance Estimate", but I would like the selection process to be based upon the Type 3 p-values with "Sandwich Variance Estimate", to control for the clustering. The DETAILS keyword in the MODEL statement will print the results from each iteration along with the different sets of p-values (if you specify COVM along with COVS(AGGREGATE) in the PHREG statement). My question: Is there a way I can change what appears to be the default behavior of the SELECTION= option and use the p-values from the Sandwich Variance Estimate? I could do the selection manually without the SELECTION= option by calling PHREG over and over again, but it would be nice if I could utilize the built-in model selection tools. Here is the basic code I am using. Thank you! PROC PHREG DATA=myData COVS(AGGREGATE) COVM;
CLASS controlVar classVar1 classVar2;
MODEL Days*Outcome(0)=controlVar classVar1 classVar2 numVar1 numVar2
/ TIES=EXACT RL=WALD INCLUDE=1 START=100 SELECTION=STEPWISE
SLE=0.05 SLS=0.05 TYPE3(WALD) DETAILS;
ID mouseID;
RUN; controlVar - A classification variable to be included in all models classVar1, classVar2 ... - Classification variables of interest as prognostic factors numVar1, numvar2 ... - Continuous numeric variables of interest as prognostic factors Days - Number of days until the outcome or censoring occurs Outcome - Equal to 1 if the outcome occurs in the eye or 0 if the eye is censored (no outcome before end of observation) mouseID - Unique identifier of a study participant SAS Version: SAS/STAT 13.1
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