Chapter 3
Binary Logistic Regression: Details and Options
3.3 Details of Maximum Likelihood Estimation
3.6 Goodness-of-Fit Statistics
3.7 Statistics Measuring Predictive Power
3.9 Predicted Values, Residuals, and Influence Statistics
3.10 Latent Variables and Standardized Coefficients
3.11 Probit and Complementary Log-Log Models
3.13 Sampling on the Dependent Variable
3.14 Plotting Effects of Predictor Variables
3.1 Introduction
In this chapter, we continue with the binary logit model and its implementation in PROC LOGISTIC. We'll examine several optional features of this procedure, consider ...
Get Logistic Regression Using SAS, 2nd Edition now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
