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University:  University of California, San Diego - UCSD

Greek Organization:  Pi Kappa Alpha

Author:  Sebastian

Comment:  Model Comparison: Pseudo � 2 R 2 can be useful for comparing different logistic regression models on the same dataset. A higher pseudo � 2 R 2 usually indicates a better fit. Assessing Improvement: When you add or remove predictors from the model, pseudo � 2 R 2 can help you assess whether the model's fit has improved. Not for Explained Variance: It should not be used as a measure of the proportion of variance explained by the model, as it doesn't have the same interpretation as � 2 R 2 in linear regression. Not for Isolated Interpretation: Pseudo � 2 R 2 values are generally not useful for interpreting the quality of a model in isolation. They are more useful when comparing different models for the same dataset.