Hi, I’m sorry, I know that it is a recurrent question but I have not been able to find the response in the Rhelp archives. I think my data require the use of the glmmPQL function but I do not know how to make the model selection. Since the AIC and log-likelihood are apparently meaningless, how can we select the parameters for a model and compare the models to find which one fits best the data? Thanks a lot Emmanuelle Tastard Emmanuelle TASTARD UMR 5174 'Evolution et Diversité Biologique' Université Paul Sabatier Bat 4R3 31062 TOULOUSE CEDEX 9 France tel : 05 61 55 67 59 [[alternative HTML version deleted]]
Emmanuelle TASTARD <tastard <at> cict.fr> writes:> > Hi, > I伮抦 sorry, I know that it is a recurrent question but I have not been > able to find the response in the Rhelp archives. > I think my data require the use of the glmmPQL function but I do not > know how to make the model selection. Since the AIC and log-likelihood > are apparently meaningless, how can we select the parameters for a model > and compare the models to find which one fits best the data?I think your choices are (1) use the estimated standard errors/p-values of the fixed effects to decide whether to include them in the model or (2) if you really need likelihood-based tests, use lmer. (Model selection for variance parameters is a can of worms, see Pinheiro and Bates.) Also remember that *all* methods for this kind of model are approximations, it's just a question of which ones are more accurate (generally and in particular situations). That's just my best guess, someone else may have better advice ... cheers Ben Bolker
Sorry for the late reply. Just use the first 90% of your data to fit and then predict the last 10% and see which one is better. If the random effects are not good it will become very obvious. If the concern is with fixed effects then just use gls which puts the random effects in the error and select model as usual. Emmanuelle TASTARD wrote:> > Hi, > I?m sorry, I know that it is a recurrent question but I have not been > able to find the response in the Rhelp archives. > I think my data require the use of the glmmPQL function but I do not > know how to make the model selection. Since the AIC and log-likelihood > are apparently meaningless, how can we select the parameters for a model > and compare the models to find which one fits best the data? > Thanks a lot > Emmanuelle Tastard > > Emmanuelle TASTARD > UMR 5174 'Evolution et Diversit? Biologique' > Universit? Paul Sabatier Bat 4R3 > 31062 TOULOUSE CEDEX 9 France > tel : 05 61 55 67 59 > > > [[alternative HTML version deleted]] > > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html >-- View this message in context: http://www.nabble.com/glmmPQL-model-selection-tp3027224p25151417.html Sent from the R help mailing list archive at Nabble.com.