Hello R-Users,
I am using glmmPQL (library MASS) on time-series count data that are aggregated
by zipcode. My model includes natural cubic splines for season and day-of-week
as fixed effects and random intercept term for zipcode. I need to extract the
fitted values AND the standard error of the fit to compute confidence intervals
for the fitted value. I am able to extract the fitted, but the predict function
doesn't work like it does for GLM [predict(glm_obj, se.fit=T)]. Is there an
equivalent for glmmPQL? Or is there some other way I can extract se?
Would also be good to know if this is not possible and there is an alternate
glmm model I can consider.
Thank you!
Ramona
Ramona Lall, PhD
City Research Scientist
Bureau of Communicable Diseases
New York City Department of Health and Mental Hygiene
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
