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Thread: Estimating a proportion from a GEE model or GLMM model

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    Estimating a proportion from a GEE model or GLMM model




    Hello all,

    I had a single sample of a binary outcome (success / failure), and I wanted to estimate the population proportion with a point estimate and a confidence interval. The problem was that some subjects contributed 2 samples, while others just 1, so my observations, or at least some of them, weren't independent.

    To solve this problem, I ran both a GEE model and a GLMM model. I used the binary outcome as a dependent variable, and a vector of 1's as an independent variable, making the intercept my interest. I thought that it would give me the proportion I look for. The vector of 1's was declared in SAS as a classification variable.

    And now for the problem. When I used the logit link function, I did not get the correct results. When I used the log link function, I did. I thought that the log link function suits the Poisson model, so I am confused. I suspect it might have something to do with the difference between proportion and predicted probabilities, but I ain't sure. I wanted to ask if someone can explain to me (and maybe please attach a formula) why the log link function is what I want here ? To be more specific, if b is the estimate of the coefficient of the intercept, I did at first e^b/(1+e^b), which was wrong. When I did e^b, it was correct. I need to know why...

    My SAS code was:

    proc genmod data = data descending ; class ID D; * D is vector of 1's model Y = D / dist = bin link=log cl ; repeated subject= ID; lsmeans D/ cl exp; run;

    Thank you very much !

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    Re: Estimating a proportion from a GEE model or GLMM model


    Maybe it has something to do with the fact that it is an intercept only model...

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