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I am struggling interpreting sigma in a random effect panel probit regression and why is this term strongly significant. I understand all the others results from the regressions.

I used the following fit call :

 Model<-pglm(Variable_to_explain ~ fv + context + male + context*male,
                model=("random"), 
                effect=("twoways"), 
                index=c("indiv", "period"), 
                family=binomial(link="probit"), data=data)

Here is the R output from a smallest regression, but the effect of sigma remains the same.enter image description here

Any help will be very appreciated.

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  • $\begingroup$ What is the fit call? and what package is the fit function in? $\endgroup$ – Stop Closing Questions Fast Sep 25 '19 at 8:22

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