I am working on my thesis analysis, and I have some error data that's right-skewed. I log-transformed it and ran glm on it (gaussian, identity in R) weighted by sample size, and my data is still over-dispersed. I keep seeing comments about using the quasi family, but I'm not sure I completely understand what I'm doing. I tried it out, and my question is, can I use quasi with the log-transformed data and still set my variance equal to my mean (or mean squared), or is that like a double variance stabilizer? If I run the data with quasi, link identity, variance = mean in R, I get approximately the same results, except the data appears to by neither under nor over-dispersed.