I have been told that reporting the Type III p-values is preferred over the GEE p-values as the type III p-values are more conservative. However, in my situation, the type III p-value is smaller than the GEE p-value. I have 2 questions in regards to this issue: 1) I am using manual backwards stepwise elimination to remove variables if P>0.05. In this example, My GEE p-value for Parity is 0.0904 yet the Type III p = 0.0407. Which p-value should I rely on to remove variables from my model? 2) I am reporting the risk ratio and confidence interval found in the lsmeans. If I am using/reporting the type III p-value, this p-value is not reflected in the RR and confidence interval. Is there a way of estimating the lsmeans and RR using the type III p-value? You can see in this example, the RR for parity is 1.9234 and the confidence interval is 0.9021 to 4.1010, which crosses 1 and therefore would not reflect a P-value <0.05. If I reported the type III p-value with this RR and CI, reviewers would see this discrepancy and realize that the reported p-value can't be accurate. proc genmod data=ket; class farm parity (ref="0") bhba (ref="0"); model ket=bhba parity/ link=log dist=poisson pscale type3; repeated subject=farm/type=exch; lsmeans bhba parity/pdiff cl exp; run; This dataset containes 1398 observations, and there are 71 clusters. I am using v. 9.4. Ket, bhba, and parity are all dichotomous variables however, ket is a rare event (3.72%). Any help is appreciated. Thank you.
... View more
