Hello, I sent my query to the r-project.org mailing list first where I got told to rather send it to the r-sig-mixed-models mailing list. I hope someone can help me with my question although the r-sig-mixed-models mailing list refers to issues with using lme4 rather than the glmmPQL function from the MASS package. So here is my question: Currently I am trying to fit a generalized linear mixed model with binary outcome using the glmmPQL function in the MASS package. I was wondering, which variance-covariance structure the glmmPQL function is using by default and if it is possible to vary the variance-covariance structure with the glmmPQL function. Unfortunately I couldn't manage to find out myself. If it is possible to change it, could someone tell me how to do so? I am especially interested in a diagonal structure versus an unstructured variance-covariance structure. Thanks a lot in advance. Gerda
What is the default covariance structure in the glmmPQL function (MASS package)?
2 messages · Gerda Börner, Voeten, C.C.
2 days later
Hi Gerda, Since glmmPQL works by repeated calls to lme, it should work the same as lme does, i.e. the default random-effects parameterization is log-Cholesky with an unstructured covariance matrix. Specifying other covariance structures should work the same as in lme, e.g. random=list(grouping=pdDiag(~covariates)) for diagonal; see ?pdClasses. Good luck, Cesko -----Oorspronkelijk bericht----- Van: R-sig-mixed-models [mailto:r-sig-mixed-models-bounces at r-project.org] Namens Gerda B?rner Verzonden: vrijdag 2 februari 2018 9:58 Aan: r-sig-mixed-models at r-project.org Onderwerp: [R-sig-ME] What is the default covariance structure in the glmmPQL function (MASS package)? Hello, I sent my query to the r-project.org mailing list first where I got told to rather send it to the r-sig-mixed-models mailing list. I hope someone can help me with my question although the r-sig-mixed-models mailing list refers to issues with using lme4 rather than the glmmPQL function from the MASS package. So here is my question: Currently I am trying to fit a generalized linear mixed model with binary outcome using the glmmPQL function in the MASS package. I was wondering, which variance-covariance structure the glmmPQL function is using by default and if it is possible to vary the variance-covariance structure with the glmmPQL function. Unfortunately I couldn't manage to find out myself. If it is possible to change it, could someone tell me how to do so? I am especially interested in a diagonal structure versus an unstructured variance-covariance structure. Thanks a lot in advance. Gerda _______________________________________________ R-sig-mixed-models at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models