An adjustment for multiple comparisons can be added as an option to the LSMEANS statement in GLIMMIX, which would be my choice. @StatDave may recommend GENMOD or GEE, as there doesn't appear to be additional random effects in play, only repeated measures.
SteveDenham
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Hello, I am performing an analysis of a measure over several time points and I obtain multiple "p-values". What type of test would you recommend to adjust for multiple comparisons? Is the PROC MULTTEST for false discovery rate recommended in this case, where the next p-value seem to depend on the previous one? Below is the list of the unordered raw p-values. raw_p 0.0314 0.083 0.0516 0.0598 0.0359 0.0507 0.0273 0.0818 0.0532 0.1366 0.2206 0.3106 0.3881 0.4311 0.516 Graph Thank you for any suggestion you may have. Marcel
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VIF is for PROC REG. Check CORRB option. And @Rick_SAS wrote a blog about it - COV of estimator.
proc logistic data=sashelp.heart;
class sex;
model status=sex agechddiag ageatstart height weight diastolic/corrb;
run;
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Sorry I was late in answering @marcel , but see what I posted for Re: Clarification needed for glimmix covariance parameters test. The answer is not to pick the simplest, but to pick the one that retains the most information (based on AIC or corrected AIC), so long as that structure is appropriate for the data generating process.
SteveDenham
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Hi, you could save your excel files as "xx.csv" files and that should give no problem at all. At the sas interface click on the pull down 'file" menu, choose "import data" and navigate to the location of your csv file. Follow the indicated next steps from the import wizard pop-up menu and the importing of the file will go smoothly. .
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Sir StatsMan, It looks that the residuals are not really "out of whack". It seems reasonable to decided that the residuals do not violate the assumption of normality. Thank you for your advise. Regards, Marcel
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I wanted to make it clear that that I found a solution to my question from two members' comments: 1) paigeMiller and 2) sld. I just do not know how to accept two sources as part of a single solution. Sorry about this. regards, marcfel
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Mr. Ksharp, Thank you for your answer. Size-wise, my sample is fine (compared to the examples in this note). I will take a look at LASSO. Isn't the SLICE option used to explore interactions? Regards, Marcel
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You can use PROC REG, and that is in fact what is done in the note I referred to. But as described there, proper evaluation of collinearity in a logistic model requires a weighted analysis in PROC REG. I encourage you to carefully and fully read through the collinearity section. PROC GENMOD is used to produce the necessary weights for a variety of model types. In the case of a logistic model, the necessary weights are just p*(1-p), so they could be produced from saving the predicted probabilities from the fitted model followed by a DATA step to compute these weights.
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Mr. StatDave, Thank you very much for your answer. It clarified for me several aspects of the analysis. I will try your suggestions. It seems that keeping it simple is one of the safest ways to go. Regards, marcel
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Your issue is the path. You're trying to access your local data but it appears SAS is running on a server.
You can likely use the GUI tools to import or you need to move your file to the server. Or you need to explain your set up in more detail and we can offer alternatives.
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