In the paper "Including Transfer-Out Behavior in Retention Models: Using the NSLC Enrollment Search Data"
the author compares two models of student retention:
- A binary logistic regression (with DV coded as either retained/not retained)
- A multinomial logistic regression (with DV coded as retained/not retained/transferred out)
The author uses two criteria for model comparison (p.14):
- "Predictive ability" measured by the the log likelihood and model chi-square
- "Explanatory power" which is a comparison of which IVs were predictive in each model, and the change in probability associated with a change in each IV.
Based on the goal of the study I understand why criteria #2 is useful for comparison. However, I am wondering if it is correct to compare likelihood ratios between these two types of models. Additionally, are there any other tests that could accurately compare logistic vs. multinomial models?