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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