A Comparison of Logistic Regression Pseudo R2 Indices

#Methods #R2 #Logit

A Comparison of Logistic Regression Pseudo R2 Indices

Key takeaways

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Bibliography: Smith, T.J., McKenna, C.M., 2013. A Comparison of Logistic Regression Pseudo R2 Indices 39.

Authors:: Thomas J Smith, Cornelius M McKenna

Collections:: Methods

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(08/05/2024, 22:00:56)

“Although pseudo R2 values for logistic regression are available as output in most statistical packages and are often reported in practice, few if any guidelines exist for their interpretation. The present study suggested that the most commonly used pseudo R2 indices (e.g., McFadden’s index, Maddala / Cox-Snell index with or without Nagelkerke correction) yield lower estimates than their OLS R2 counterparts,” (Smith and McKenna, 2013, p. 8)

“evidence that is consistent with prior simulation studies (e.g., Hagle & Mitchell, 1992; Veall & Zimmermann, 1994). This suggests that the use of guidelines intended for interpretation of the latter (e.g., Cohen, 1988) may not be appropriate for interpreting pseudo 2 R values.” (Smith and McKenna, 2013, p. 9)