[R] glmmPQL question!

[Spencer Graves]

  I don't think there is an easy way to do that. If it were my problem, 
I think I'd start by trying to the model using 'lmer' associated with 
the 'lme4' package. I would then try to pass the fit to 'mcmcsamp' to 
get a random sample of parameter estimates following the posterior 
distribution. Then I'd convert the simulated parameters into a 
distribution of predictions for the conditions of interest. While doing 
this, I'd apply "quantile" of the distribution of predictions for each 
set of conditions to get the desired confidence limits.

Make sense?

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Hope this helps.
Spencer Graves

m-krutky at northwestern.edu wrote:
> Hello Folks- 
>
> Is there a way to create confidence bands with 'glmmPQL' ??? 
>
> I am performing a stroke study for Northwestern University in Chicago, Illinois.  I am trying to
> decide a way to best plot the model which we created with the glmmPQL function in R.   I would like 
> to plot my actual averaged data points within 95 % confidence intervals from the model. Plotting
> the model is easy, but determining confidence bands is not. 
>
> Here is my model:
>
> ratiomodel<-glmmPQL(ratio~as.factor(joint)*time, random = ~ 1 | subject, family = Gamma(link =
> "identity"),alldata3)
>
> I am used to seeing confidence intervals from models that increase, “flair out” in the y direction, 
> at the beginning and ending time points (x values) of the simulated data.  If I use 'lm' and pass
> the command 'int = "c" ' 'to create this model I can easily find and plot this type of confidence
> band for 'ratio~time'.  But I need to take into account 'as.factor(joint)', and in fact I can
> produce confidence bands with 'glm' by passing in 'se.fit = TRUE', but the problem is I need to
> make subject a random variable, and take into account my ratio with the Gamma distribution.  
>
> Is there a way to create confidence bands with 'glmmPQL' ??? ' as.factor(joint)' has 3 levels, so I 
> would like to produce this linear model with three levels and confidence bands for comparison of
> the levels of 'joint'.  
>
> Any Help at all with my problem would be greatly appreciated!!
> LJ
>
>   
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