Interpreting and Comparing Effects in Logistic, Probit, and Logit Regression

This book has very clear, pristine explanations of topics such as how DRMs work, great numerical methods for maximizing and specifying, and helpful explanatory tests and interpretative effects, all written at an intermediate level. The discussion of various ways of interpreting coefficients in each of the models is the most useful part of the text. While many other texts touch on the difficulties of interpreting coefficients and perhaps offer an approach or two, the authors of this volume thoroughly review multiple approaches common and unique to each of the models.

• Chapter 1. IntroductionPurpiseContentCausalityChapter 2. Regression Models for A Dichotomous Dependent VariableIntroductionDiscrete Response Model — DRMLatent Variable Model — LVMInserting Mavericks, “Orthogonal” Independent Variables, Into EquationsChapter 3. Interpreting And Comparing Effects Within One EquationComparing Effects Within a Single LVM EquationComparing Effects Within a Single DRM EquationCausal Interpretations in LVM and DRM Logistic RegressionChapter 4. Comparing Subgroups Or Time Points: Investigating Interaction EffectsInteraction Effects in LVMInteraction Effects in DRMInteraction and Causal AnalysisChapter 5. Causal Modeling: Estimating Total, Direct, Indirect And Spurious Effects; Using Effect Coefficients From Different (Nested) EquationsIntroductionLVMDRMCasual ModelingChapter 6. Concluding Remarks; Extensions, Effect Measures And EvaluationPolytomous Dependent VariableHow to Measure Effects in Logistic RegressionConcluding Remarks