search for: glmpql

...siliy 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...

...eviance and df). summary(fm.1 <- glm(cbind(response, 100 - response) ~ expt, data = data.1, family = binomial)) summary(fm.2 <- glm(response ~ expt, data = data.2, family = binomial)) However, if I estimate these two equations as a mixed model using glmPQL, I get completely different results between the two specifications, fm.3 and fm.4. Which one is right? The example which accompanies help(glmmPQL) suggests fm.4. summary(fm.3 <- glmmPQL(cbind(response, 100 - response) ~ expt, data = data.1, random = ~ 1 | subject,...

...odel with Wald t or F statistic (since it is non-normal, can?t be transformed to normality, has a mean < 5, has less than 3 random effects, and is overdispersed). I?m using the glmer {lme4} function, since it allows for Laplace or GHQ, as well as more than one random factor (glmmML {glmmML) and glmPQL {MASS} apparently does not), as follows: > m1<-glmer(Seedlings~N*G*(1|Year)*(1|Site), data=ex5m, family=poisson(link="log")) My questions are: 1) The model returns Z values, and I?m unable to find an argument in the function where this can be changed to return a t or F value (as Bo...

...odel with Wald t or F statistic (since it is non-normal, can?t be transformed to normality, has a mean < 5, has less than 3 random effects, and is overdispersed). I?m using the glmer {lme4} function, since it allows for Laplace or GHQ, as well as more than one random factor (glmmML {glmmML) and glmPQL {MASS} apparently does not), as follows: > m1<-glmer(Seedlings~N*G*(1|Year)*(1|Site), data=ex5m, family=poisson(link="log")) My questions are: 1) The model returns Z values, and I?m unable to find an argument in the function where this can be changed to return a t or F value (...

...a) How to set the level 2 covariates (V2, V3) nested within student (V1) in the model below, is the nesting of students within universities correct as (1|V8) for the random intercept? model <- lmer(V9 ~ V4 + V5 + V6 + ?.+ (1|V8) ???, data=datos, family = "binomial") or should I use ?glmPQL? b) Do I need to change any coding in the column(s) of the data file? Any help would be greatly appreciated. Sincerely, Rafael Diaz Assistant Professor Dept of Mathematics and Statistics California State University Sacramento