Hi, I'm running a GLMM on binomial choice data. The outputs I receive are sensible except for the degrees of freedom, which come out much larger than expected. Can anyone advise please? Exptl design: Response = Choice Fixed Factors = Position, Treatment and Sex Random Factor = ID nested within Treatment and Sex Covariate = Delay The model: glmmPQL(FreeChoice ~ Position * Treatment + Sex + Delay, random = list(~Sex + Treatment|Name), family = binomial) Thanks, Mark ------------------------------------------------------------------------ Mark Steer School of Biological Sciences University of Bristol Woodland Road Bristol, BS8 1UG tel - ++44 (0)117 9545945 (int. 45945)
GlmmPQL help
2 messages · Mark Steer, Spencer Graves
1 day later
Have you received a reply to this question? If you still want an answer, please submit a much simpler, self-contained example that someone can copy from your email into R, examine possibly with other tools and offer comments in a minute or two. Please include the output, labeling clearly the degrees of freedom in question, what you think the number should be and why. I believe that will increase the chances that you will get a useful reply quickly. I'm sorry I couldn't help more. spencer graves
Mark Steer wrote:
Hi, I'm running a GLMM on binomial choice data. The outputs I receive are sensible except for the degrees of freedom, which come out much larger than expected. Can anyone advise please? Exptl design: Response = Choice Fixed Factors = Position, Treatment and Sex Random Factor = ID nested within Treatment and Sex Covariate = Delay The model: glmmPQL(FreeChoice ~ Position * Treatment + Sex + Delay, random = list(~Sex + Treatment|Name), family = binomial) Thanks, Mark ------------------------------------------------------------------------ Mark Steer School of Biological Sciences University of Bristol Woodland Road Bristol, BS8 1UG tel - ++44 (0)117 9545945 (int. 45945)
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