What is a good McFadden pseudo R-squared?

What is a good McFadden pseudo R-squared?

A rule of thumb that I found to be quite helpful is that a McFadden’s pseudo R2 ranging from 0.2 to 0.4 indicates very good model fit.

What package is pseudo R2 in R?

Nagelkerke’s R^2 (also sometimes called Cragg-Uhler) is an adjusted version of the Cox and Snell’s R^2 that adjusts the scale of the statistic to cover the full range from 0 to 1. McFadden’s R^2 is another version, based on the log-likelihood kernels for the intercept-only model and the full estimated model.

What should pseudo your 2 be for McFadden’s regression?

A rule of thumb that I found to be quite helpful is that a McFadden’s pseudo R 2 ranging from 0.2 to 0.4 indicates very good model fit. As such, the model mentioned above with a McFadden’s pseudo R 2 of 0.192 is likely not a terrible model, at least by this metric, but it isn’t particularly strong either.

What is the interpretation of this pseudo R-squared?

What is the interpretation of this pseudo R-squared? Is it a relative comparison for nested models (e.g. a 6 variable model has a McFadden’s pseudo R-squared of 0.192, whereas a 5 variable model (after removing one variable from the aforementioned 6 variable model), this 5 variable model has a pseudo R-squared of 0.131.

What is the definition of McFadden’s your squared?

McFadden’s R squared is defined as 1-l_mod/l_null, where l_mod is the log likelihood value for the fitted model and l_null is the log likelihood for the null model which includes only an intercept as predictor (so that every individual is predicted the same probability of ‘success’).

Where does pseudo R2 between 0.2 and 0.4 come from?

The interpretation of McFadden’s pseudo R2 between 0.2-0.4 comes from a book chapter he contributed to: Bahvioural Travel Modelling. Edited by David Hensher and Peter Stopher. 1979. McFadden contributed Ch. 15 “Quantitative Methods for Analyzing Travel Behaviour on Individuals: Some Recent Developments”.