Pseudo R Squared. McFaddens Pseudo R-Squared adjusted. Nagelkerkes R squared This pseudo R squared is very similar to Cox-Snells R squared.
Psuedo r-squared for logistic regression. A pseudo R-squared is not directly comparable to the R-squared for OLS models. Pseudo R-Squared Measures In the linear regression model the coefficient of determination R 2 summarizes the proportion of variance in the dependent variable associated with the predictor independent variables with larger R 2 values indicating that more of the variation is explained by the model to a maximum of 1.
Instead pseudo R-squared measures are relative measures among similar models indicating how well the model explains the data.
If you call DiscreteResultsprsquared you will get the value of McFaddens R-squared value on your fitted nonlinear regression model. Numerous pseudo r-squared measures have been proposed for generalized linear models involving a comparison of the log-likelihood for the fitted model against the log-likelihood of a nullrestricted model with no predictors normalized to run from zero to one as the fitted model provides a better fit to the data providing a rough analogue to the computation of r-squared in a linear regression. In ordinary least square OLS regression the R2 statistics measures the amount of variance explained by the regression model. R 2 adj 1 ln LLMˆ full-Kln LLMˆ intercept.
