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Can I read Regression Models for Categorical and Limited Dependent Variables (Advanced Quantitative Techniques in the Social Sciences) on EtoBox?

Regression Models for Categorical and Limited Dependent Variables (Advanced Quantitative Techniques in the Social Sciences) by Long, John Scott is a mathematics available to read on EtoBox.

What is Regression Models for Categorical and Limited Dependent Variables (Advanced Quantitative Techniques in the Social Sciences) about?

A unified treatment of the most useful models for categorical and limited dependent variables (CLDVs) is provided in this book. Throughout, the links among the models are made explicit, and common methods of derivation, interpretation and testing are applied. In addition, the author explains how models relate to linear regression models whenever possible. After a review of the linear regression model and an introduction to maximum likelihood estimation, the book then: covers the logit and probit models for binary outcomes; reviews standard statistical tests associated with maximum likelihood estimation; and considers a variety of measures for assessing the fit of a model. J. Scott Long also: extends the binary logit and probit models to ordered outcomes; presents the multinomial and conditioned logit models for nominal outcomes; considers models with censored and truncated dependent variables with a focus on the tobit model; describes models for sample selection bias; presents models for count outcomes by beginning with the Poisson regression model; and compares the models from earlier chapters, discussing the links between these models and others not discussed in the book

Who reads Regression Models for Categorical and Limited Dependent Variables (Advanced Quantitative Techniques in the Social Sciences)?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Long, John Scott
Publisher
Sage Publications; Sage Publications, Inc
Published
1997
Language
EN
ISBN
9780803973749
Category
mathematics
Subjects
Mathematics, Stem
Rating
4.7 / 5 (32 ratings)
Updated
2026-03-14

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