Hello everyone,
I have a question about geeglm function in the GEE package in R. I am a begginner in statistics and the estimates in the output of the model are puzzling me. How can I tell that the estimates are ok and how can I recognise overdispersion?
the output looks like this:
Estimated Scale Parameters:
Estimate Std.err
(Intercept) 0.8 0.08
Correlation: Structure = ar1 Link = identity
Estimated Correlation Parameters:
Estimate Std.err
alpha 0.7 0.05
Number of clusters: 24 Maximum cluster size: 16
Thank you for any feedback or suggestions.
Have a great day
Misa
What is the probability distribution you use this case for the variable response? With this, you can check the presence or absence of overdispers or underdispersion. You can still use residual graphs that will help you in the diagnosis of your model.
To see if your estimates are ok, you calculate (estimate/std.error) to get a z-value to compare with 2, to find if your estimates are significant.
Did you look for another output option in R? It should inform you about overdispersion.
Thank you both for answers, I am using gaussian distribution,I have checked the fitted vs residuals plot if the values are scattered and it looks okay.
I have checked the z values as you suggested and they are: intercept -1.812, factor 1= 5.705, factor 2 = -2.121, factor 3= -4.115, now I am not really sure what that means. can you advice me? thank you very much!
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