Hello!

I am trying to find the right model that matches the distribution of my data. I use cross-sectional data and I want to explain life satisfaction ("0=not satisfied at all - 10=completely satisfied) by social relationships (marital status, social network size). My dependent variable is negatively skewed (-1.16). After running my OLS regression (including control variables), I find that my residuals are also not normally distributed. The residual-vs.fitted plot indicates heteroskedasticity. I also checked both the Breusch-Pagan / Cook-Weisberg test and the White's test for heteroskedasticity which are both highly significant (Prob > chi2 = 0.0000). I also tried to transform my dependent variable but I don't see an improvement after doing a log-transformation or Box-Cox transformation.

Rather than forcing the data to fit the model, I am now trying to find the right family and link for a generalized linear model. I think that family(gamma) and link(log) could fit my data. But mostly I have no clue (yet) how to find out. Can you give me a hint?

Thank you very much!

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