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Using Predictions and Marginal Effects to Compare Groups in Regression Models for Binary Outcomes

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TLDR
Methods for group comparisons using predicted probabilities and marginal effects on probabilities are developed for regression models for binary outcomes and how this interpretive framework can be used with a broad class of regression models and can be extended to any number of groups is considered.
Abstract
Methods for group comparisons using predicted probabilities and marginal effects on probabilities are developed for regression models for binary outcomes. Unlike approaches based on the comparison ...

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Best Practices for Estimating, Interpreting, and Presenting Nonlinear Interaction Effects

TL;DR: In this paper, the authors synthesize an evolving methodological literature and provide straightforward advice and techniques to estimate, interpret, and present nonlinear interaction effects in models for categorical outcomes.
Journal ArticleDOI

Structural Sexism and Health in the United States: A New Perspective on Health Inequality and the Gender System:

TL;DR: In this paper, a new line of health inequality research that parallels the emerging structural racism literature is built, and the concept of structural sexism and structural racism is developed. But, it is not discussed in this paper.
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A General Framework for Comparing Predictions and Marginal Effects across Models

TL;DR: The authors provide a general framework for comparing predictions and marginal effects across models using seemingly unrelated estimation to combine estimates from multiple models, which allows tests of the equality of predictions and effects across Models.
Journal ArticleDOI

Latinos’ deportation fears by citizenship and legal status, 2007 to 2018

TL;DR: Whether and how Latinos’ deportation fears vary by citizenship and legal status and over time is examined, highlighting how deportation or its consequences affects a racial group that the US immigration regime targets disproportionately.
References
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Book

Limited-Dependent and Qualitative Variables in Econometrics

G. S. Maddala
TL;DR: In this article, the authors present a survey of the use of truncated distributions in the context of unions and wages, and some results on truncated distribution Bibliography Index and references therein.
Book

Regression Models for Categorical and Limited Dependent Variables

TL;DR: In this article, the authors propose Continuous Outcomes Binary Outcomes Testing and Fit Ordinal Outcomes Numeric Outcomes and Numeric Numeric Count Outcomes (NOCO).
Journal ArticleDOI

Interaction terms in logit and probit models

TL;DR: In this article, the authors present the correct way to estimate the magnitude and standard errors of the interaction effect in nonlinear models, which is the same way as in this paper.
Book

Discrete multivariate analysis: theory and practice

TL;DR: Discrete Multivariate Analysis is a comprehensive text and general reference on the analysis of discrete multivariate data, particularly in the form of multidimensional tables, and contains a wealth of material on important topics.
Journal ArticleDOI

Regression Models for Categorical and Limited Dependent Variables

James A. Calvin
- 01 Feb 1998 - 
TL;DR: Introduction Continuous Outcomes Binary Outcomes Testing and Fit Ordinal Outcomes Nominal outcomes Limited Outcomes Count Outcomes Conclusions
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