Hello Statalist,
I am having some issues analyzing data with glm. I have tried several
methods to analyze my zero-inflated data set (zinb, hurdle and glm).
The best model fit that I get are when I log transform the response
variable prior to analysis with a glm model using a negative binomial
distribution. The negative binomial uses a log link function, so I
think that this analysis is essentially double log-transforming the
data, once initially, and then when the response is linked to the
predictors it is log-transformed again. I have not been able to find
any literature regarding this, so I was wondering if anyone knows if
this is an appropriate way to analyze these data? Does it violate
assumptions of the glm?? Thanks for your time.
Chuck
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