Timeline for Interpreting dispersion parameters of poisson GLMM with count data
Current License: CC BY-SA 3.0
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| Jul 21, 2016 at 20:18 | comment | added | Robert Long | @tri I'm not a fan of rules of thumb. They have a tendancy to become de facto rules, like p < 0.05 or rmsea < 0.05 or TLI > 0.9 etc etc. With 24 groups and 90 observations your sample isn't enormous, but you could get a parametric and/or semi-parametric bootstrap estimate of the confidence interval for the ratio, and see if it's upper bound is over 1 in which case you can be happy. Also try a CMP model as I suggested and compare it with the poisson glmm and a regular poisson glm | |
| Jul 21, 2016 at 16:48 | comment | added | tri | Thank you @RobertLong. This is good food for thought (although I have some work to do before I will understand all of it). Also, you picked up an error in my code. I re-worked it and edited my post so you'll see I have 90 observations, not 24 as noted earlier. I also re-did my residual plot. I am curious to know if this changes any of your ideas on this. I have a difficult time understanding what qualifies as a "not very small" dispersion ratio. Are there any rules of thumb for interpreting these things? | |
| Jul 20, 2016 at 13:47 | history | answered | Robert Long | CC BY-SA 3.0 |