Generalized linear models : a unified approach

書誌事項

Generalized linear models : a unified approach

Jeff Gill, Michelle Torres

(Sage publications series, . Quantitative applications in the social sciences ; 134)

Sage, c2020

2nd ed

  • : pbk

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注記

Includes bibliographical references and index

内容説明・目次

内容説明

Generalized Linear Models: A Unified Approach provides an introduction to and overview of GLMs, with each chapter carefully laying the groundwork for the next. The Second Edition provides 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. Software scripts, supporting documentation, data for the examples, and some extended mathematical derivations are available on the authors' websites as well as through the \texttt{R} package \texttt{GLMpack}. Supporting material (data and code) to replicate the examples in the book can be found in the 'GLMpack' package on CRAN or on the website&

目次

Series Editor's Introduction About the Authors Acknowledgements 1. Introduction Model Specification Prerequisites and Preliminaries Looking Forward 2. The Exponential Family Justification Derivation of the Exponential Family Form Canonical Form Multi-Parameter Models 3. 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 4. Linear Structure and the Link Function The Generalization Distributions 5. Estimation Procedures Estimation Techniques Profile Likelihood Confidence Intervals Comments on Estimation 6. Residuals and Model Fit Defining Residuals Measuring and Comparing Goodness-of-Fit Asymptotic Properties 7. Extentions 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 Accomodating Models A Warning About Robust Standard Errors Summary 8. Conclusion Summary Related Topics Classic Reading Final Motivation 9. References

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詳細情報

  • NII書誌ID(NCID)
    BB2855370X
  • ISBN
    • 9781506387345
  • LCCN
    2019007059
  • 出版国コード
    us
  • タイトル言語コード
    eng
  • 本文言語コード
    eng
  • 出版地
    Los Angeles
  • ページ数/冊数
    xi, 157 p.
  • 大きさ
    22 cm
  • 分類
  • 件名
  • 親書誌ID
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