I am new to negative binomial regression and am using Generalized Linear Models in SPSS to analyze some highly skewed count data (it is not zero inflated and the variance is much higher than the mean so I'm not using Poisson regression).
I'm interested in the extent to which shared variance among the predictors may be causing some predictors to be non-significant in the final model. My supervisor has used commonality analysis to address this in linear regression and I'm curious whether there is something comparable that I could use given that R square is not available for negative binomial regression. Any suggestions for SPSS or other programs? Thanks!