My logistic regression model has a binomial response and 3 categorical predictors, A, B and C.
The observations are clustered under a factor R. There are 50 clusters based on R. Because of this clustering structure, I am using PROC GENMOD in SAS with the REPEATED statement. Thus, I am using generalized estimating equations to estimate the regression coefficients.
When I ask for the Type-3 analysis in the MODEL statement, I can use the default score test or the Wald test. Unfortunately, they give very different P-values.
Here are the P-values from the score test.
Here are the P-values from the Wald test.
I want to determine if B and C are significant predictors of the response, but these contrasting Type-3 results confuse me.
My questions:
1) Which test should I use to evaluate the significance of the predictors?
2) Could these contrasting results be a sign that the model is invalid for my data set? If so, are there other ways to check the validity of my model?
According to documentation. Wald test is based on Normal distribution approximation ( which usually unbias), while Score test is based on Likelihood (bias).
When you have a big data, both of them are going to have the same value .but if your data is small , they are going to be different .
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