log likelihood tests
Hi Katie, I'm not sure that this is the best group to send that question to, as it's a list serve dedicated to mixed-effects modeling questions in R, not SAS. I am under the impression that similar list serves exist for SAS. I recommend that you try those in the first instance. That said, there may be someone in this group with experience of SAS. I don't have any. Good luck, Andrew
On Fri, Dec 09, 2011 at 03:05:56PM -0600, Katie McGhee wrote:
Dear mixed model list serve group, I was wondering if anyone could advise me on the significance testing of random effects in a generalized linear mixed model? I am a biologist with basic statistical knowledge and since I am using a complex method, I want to make sure that I am doing things correctly. My experiment: I performed a paternal half-sib breeding design to examine whether a variety of mating and non-mating behaviors are significantly heritable. I am interested in whether "sire" explains a significant amount of the behavioral variation. My analysis: The behavioral data was non-normal and had a lot of zeros, so I decided to try a GLMM. I conducted my analysis in SAS GLIMMIX with sire and dam(sire) as random effects and no fixed effects. I specified a negative binomial distribution with a log link function and used the Laplace approximation to get a true log-likelihood. My question: When I want to figure out whether my random effect of sire is significant, do I compare models with and without the sire effect in their -2 log likelihoods under the "Fit Statistics" or the -2 log likelihood (behavior | random effects) under the "Fit Statistics for conditional distribution"? Both of these things are included in the SAS output. I am confused because I have seen some statistics papers (way over my head so I may be totally off-base here, e.g.Paul and Deng 2000) that suggest using the conditional distributions for sparse data (which mine is). I have also analyzed my zero-rich data as binomial (scored as 1/0, binomial distribution, probit link function, laplace estimation) which seems much more appropriate and the conclusions in terms of the significance of sire match better with those from the log likelihood tests using the conditional distribution than the regular log likelihood test from the marginal distribution. I apologize if this is super obvious but I have searched SAS discussions,etc and as of yet, I can find no straightforward answer. I would appreciate any help you could offer! Thank you! Sincerely, Katie -- ---- ><((((?> ----------- ><((((?> ---- Katie E. McGhee Postdoctoral Fellow Integrative Biology University of Illinois 433 Morrill Hall 505 S. Goodwin Ave. Urbana, IL, 61801 kemcghee at illinois.edu [[alternative HTML version deleted]]
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