How does Stata calculate the pseudo R squared that it displays after logistic regression and how is it best interpreted?
Maybe this webpage could help
https://stats.oarc.ucla.edu/other/mult-pkg/faq/general/faq-what-are-pseudo-r-squareds/
This attached paper is the standard work on the subject. Basically a pseudo R ** 2 has little meaning.. you can forget it in most analyses. Best wishes David Booth
https://www.graphpad.com/guides/prism/latest/curve-fitting/reg_mult_logistic_gof_pseudo_r_squared.htm
https://stats.oarc.ucla.edu/other/mult-pkg/faq/general/faq-what-are-pseudo-r-squareds/#:~:text=A%20pseudo%20R%2Dsquared%20only,model%20better%20predicts%20the%20outcome.
Think these link will be helpful to you!!
This is McFadden's R^2 (Stata calls it Pseudo R squared) and is a measure of goodness of fit. Usually 0.2 - 0.4 indicates very good fit
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