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gill j torres m generalized linear models unified approach 2019

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Textbook in PDF format Generalized Linear Models: A Unified Approach provides an introduction to and overview of GLMs, with each chapter carefully laying the groundwork for the next. Authors Jeff Gill and Michelle Torres provide examples using real data from multiple fields in the social sciences such as psychology, education, economics, and political science, including data on voting intentions in the 2016 U.S. Republican presidential primaries. The Second Edition also strengthens material on the exponential family form, including a new discussion on the multinomial distribution; adds more information on how to interpret results and make inferences in the chapter on estimation procedures; and has a new section on extensions to generalized linear models. Series Editor Introduction About the Authors Introduction Model Specification Prerequisites and Preliminaries Looking Forward The Exponential Family Justification Derivation of the Exponential Family Form Canonical Form Multiparameter Models Likelihood Theory and the Moments Maximum Likelihood Estimation Calculating the Mean of the Exponential Family Calculating the Variance of the Exponential Family The Variance Function Linear Structure and the Link Function The Generalization Distributions Estimation Procedures Estimation Techniques Profile Likelihood Confidence Intervals Comments on Estimation Residuals and Model Fit Defining Residuals Measuring and Comparing Goodness of Fit Asymptotic Properties Extensions to Generalized Linear Models Introduction to Extensions Quasi-Likelihood Estimation Generalized Linear Mixed-Effects Model Fractional Regression Models The Tobit Model A Type 2 Tobit Model With Stochastic Censoring Zero-Inflated Accommodating Models A Warning About Robust Standard Errors Summary Conclusion Summary Related Topics Classic Reading Final Motivation Endnotes References Index

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gill j torres m generalized linear models unified approach 2019

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