Applications of Regression for Categorical Outcomes Using R

This book covers the main models within the GLM (i.e., logistic, Poisson, negative binomial, ordinal, and multinomial). For each model, estimations, interpretations, model fit, diagnostics, and how to convey results graphically are provided. There is a focus on graphic displays of results as these are a core strength of using R for statistical analysis. Many in the social sciences are transitioning away from using Stata, SPSS and SAS, to using R, and this book uses statistical models which are relevant to the social sciences. Social Science Applications of Regression for Categorical Outcomes Using R will be useful for graduate students in the social sciences who are looking to expand their statistical knowledge, and for Quantitative social scientists due to it's ability to act as a practitioners guide.

Key Features:

• Applied- in the sense that we will provide code that others can easily adapt
• Flexible- R is basically just a fancy calculator. Our programs will enable users to derive quantities that they can use in their work
• Timely- many in the social sciences are currently transitioning to R or are learning it now. Our book will be a useful resource
• Versatile- we will write functions into an R package that can be applied to all of the regression models we will cover in the book
• Aesthetically pleasing- one advantage of R relative to other software packages is that graphs are fully customizable. We will leverage this feature to yield high-end graphical displays of results
• Affordability- R is free. R packages are free. There is no need to purchase site licenses or updates.

本書涵蓋了GLM（即，logistic、Poisson、negative binomial、ordinal和multinomial）中的主要模型。對於每個模型，提供了估計、解釋、模型適配度、診斷以及如何以圖形方式呈現結果的方法。本書特別關注結果的圖形展示，因為這是使用R進行統計分析的核心優勢。許多社會科學領域的人正在從使用Stata、SPSS和SAS轉向使用R，而本書使用的統計模型與社會科學相關。

《Social Science Applications of Regression for Categorical Outcomes Using R》對於希望擴展統計知識的社會科學研究生以及量化社會科學家來說，將是一本實用的資源，因為它能夠充當實踐指南。

主要特點：
- 應用性：我們將提供其他人可以輕鬆適應的程式碼。
- 靈活性：R基本上只是一個高級計算器。我們的程式將使用者能夠推導出他們在工作中可以使用的數量。
- 及時性：許多社會科學領域的人目前正在轉向使用R或正在學習它。我們的書將是一個有用的資源。
- 多功能性：我們將編寫一個R套件中的函數，可以應用於本書中涵蓋的所有回歸模型。
- 美觀：相對於其他軟體包，R的一個優勢是圖形是完全可自定義的。我們將利用這個功能來產生高端的圖形展示結果。
- 經濟實惠：R是免費的。R套件也是免費的。無需購買網站許可證或更新。

David Melamed is a Professor of Sociology and Translational Data Analytics at The Ohio State University. His research interests include the emergence of stratification, cooperation and segregation in dynamical systems, and statistics and methodology. Since 2019 he has been co-Editor of Sociological Methodology.

Long Doan is an Associate Professor of Sociology at the University of Maryland, College Park. His research examines how various social psychological processes like identity, intergroup competition, and bias help to explain the emergence and persistence of social stratification. He focuses on inequalities based on sexuality, gender, and race.

David Melamed是俄亥俄州立大學的社會學和轉譯數據分析學教授。他的研究興趣包括階層形成、動態系統中的合作和隔離，以及統計和方法論。自2019年以來，他擔任《社會方法論》的聯合編輯。

Long Doan是馬里蘭大學學院公園分校的社會學副教授。他的研究探討各種社會心理過程，如身份認同、群體競爭和偏見，以解釋社會階層的出現和持續存在。他專注於基於性取向、性別和種族的不平等現象。