Hi Reeza, thank you very much for the hint. Right now, I'm not having an discrepancy anywhere but I want to be sure that my thinking is correct, as I have to specify an analysis a-priori and want to be sure that it makes sense. If it turns out to be wrong concept-wise, that would mean some trouble My question can be re-stated more simple: The test of a parameter in a multiple logistic regression reported by default is a Wald test, so it is consistent with the default odds ratio confidence interval, the two belong together: If the p-value of the parameter is less than 5% then the 95%confidence interval of the corresponding adjusted parameter does not include 1. The question is: Is this also true for the pair of LR test and profile likelihood confidence interval? To add more detail in my case: The treatment variable is a class variable with 2 classes, the covariate is a center variable with many classes (around 20). Because the variable in question is the treatment variable, it is a class variable with 2 levels, and therefore the chi-square distribution to compare against for the LR test should be the one with 1 df, at least if I got it right psj2 PS: In SAS code, my idea looks like this: (I have let it run for some example data and it looks ok, but that were only examples ) proc logistic data=foo; class treatment center; model outcome(event="1")=treatment center; oddsratio treatment / CL=PL; ods output FitStatistics=fullmod OddsRatiosPL=ORs; run; proc logistic data=foo; class center; model outcome(event="1")= center; ods output FitStatistics=redmod; run; data bar; merge fullmod(where=(Criterion="-2 Log L") keep=InterceptAndCovariates Criterion rename=(InterceptAndCovariates=Dfull)) redmod(where=(Criterion="-2 Log L") keep=InterceptAndCovariates Criterion rename=(InterceptAndCovariates=Dred)) ORs ; pval=1-probchi(Dred-Dfull,1); keep Effect OddsRatioEst LowerCL UpperCL pval; run; proc print noobs label; run;
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