Power Calculations - Logistic Mixed Effects Model

[ahu_]

I am trying to determine the needed sample size for a Logistic Mixed Effects Model powered at 90% with a type I, alpha, error of 5%. I don't have pilot data and there aren't similar studies that have repeated measures. I do have estimates for a logistic regression without repeated measures, including an Odds Ratio of 0.83 and a response probability of 6.9%. How can I estimate my sample size in SAS?

Here is the code for the model I will be running: 

proc glimmix data=ecig method=quad oddsratio;
class ID Year(ref='2018');
model vape(Event='1')=Year /s dist=binary link=logit ddfm=none
chisq;
random intercept/subject=ID;
output out=glmxout predicted(blup ilink)=predprob;
run;

[Season]

You can search on the web for papers on this field like Estimating power in (generalized) linear mixed models: An open introduction and tutorial in R | Beha.... R code is provided in the paper.

[Season]

Another paper (Calculating power in analysis of variance. (apa.org)) found on the book Statistical Power Analysis for the Behavioral Sciences | Jacob Cohen | (taylorfrancis.com) also discusses the topic of power calculation in mixed effect models. Of closer revelance to your question is another paper cited in this book: Optimum Sample Size and Number of Levels in a One-Way Random-Effects Analysis of Variance: The Journ.... A table of optimum sample size or number of levels for the random effects model is included in the latter paper. I hope these information helps.