this is my first post. I'm truly grateful for this community.
I am trying to analyze longitudinal count data that is zero-truncated (probability that response variable = 0 is 0), and the mean != variance, so a negative binomial distribution was chosen over a poisson.
Functions/commands I've ruled out:
- gee() function in R does not account for zero-truncation nor the negative binomial distribution (not even with the MASS package loaded)
- glm.nb() in R doesn't allow for different correlation structures
- vglm() from the VGAM package can make use of the posnegbinomial family, but it has the same problem as Stata's ztnb command (see below) in that I can't refit the models using a non-independent correlation structure.
- If the data wasn't longitudinal, I could just use the Stata packages ztnb to run my analysis, BUT that command assumes that my observations are independent.
I've also ruled out GLMM for various methodological/philosophical reasons.
For now, I've settled on Stata's xtgee command (yes, I know that xtnbreg also does the same thing) that takes into account both the nonindependent correlation structures and the neg binomial family, but not the zero-truncation. The added benefit of using xtgee is that I can also calculate qic values (using the qic command) to determine the best fitting correlation structures for my response variables.
If there is a package/command in R or Stata that can take 1) nbinomial family, 2) GEE and 3) zero-truncation into account, I'd be dying to know.
I'd greatly appreciate any ideas you may have. Thank you.