Yes. On Tue, 14 Jan 2003, Maarten Speekenbrink wrote:
> Dear R-users, > > I have conducted an experiment with a 2*2*2 factorial within-subjects design. All >factors are binary and the dependent measure is a frequency of successes between 0 >and 4. Treating this as a normally distributed variable, I would perform a >repeated-measures ANOVA as follows: > > > aov(y ~ A*B*C + Error(subj/(A+B+C))) > > but since the distribution of the dependent measure is clearly nonnormal, I would >like to fit an analoguous model which is appropriate and I believe this would be a >GLMM with a logit link and a random intercept for subjects. I have fitted this model >using 'glmmPQL' function in MASS as: > > > glmmPQL(cbind(y,4-y) ~ A*B*C, random = ~ 1|subj, family=binomial(),data) > > which seemed to do the trick. But I would like to present the results in an >ANOVA-type table so that they are easiliy interpretable for the readers. I know the >anova(glm, test="Chisq") function for fixed-effect GLM gives a ANOVA-type analysis in >terms of the sequential Chi-Square difference tests, but since the glmmPQL function >returns an object of the class lme, I wonder if the results of an anova(glmPQL) are >appropriate. From an earlier posting I gathered that anova and AIC are inappropriate >for model comparisons when the models are estimated by glmmPQL, since the estimation >is not maximum likelihood, but does this hold for the anova applied to a single model? > > Kind regards, > > Maarten Speekenbrink > -------------------------------------------------------------------- > drs. M. Speekenbrink > Psychological Methodology > Department of Psychology, Faculty of Social and Behavioral Sciences > address: Roeterstraat 15, 1018 WB Amsterdam, Netherlands > tel: +31 20 525 6876 / +31 20 525 6870 > fax: +31 20 639 0026 > -------------------------------------------------------------------- > > ______________________________________________ > [EMAIL PROTECTED] mailing list > http://www.stat.math.ethz.ch/mailman/listinfo/r-help > -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ [EMAIL PROTECTED] mailing list http://www.stat.math.ethz.ch/mailman/listinfo/r-help
