An Introduction to Categorical Data Analysis, 3/e (Hardcover)
暫譯: 類別資料分析導論,第3版 (精裝本)

Agresti, Alan

  • 出版商: Wiley
  • 出版日期: 2018-11-20
  • 定價: $1,950
  • 售價: 9.8$1,911
  • 語言: 英文
  • 頁數: 400
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 1119405262
  • ISBN-13: 9781119405269
  • 相關分類: Data Science
  • 立即出貨 (庫存=1)

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商品描述

A valuable new edition of a standard reference

The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An Introduction to Categorical Data Analysis, Third Edition summarizes these methods and shows readers how to use them using software. Readers will find a unified generalized linear models approach that connects logistic regression and loglinear models for discrete data with normal regression for continuous data.

Adding to the value in the new edition is:

- Illustrations of the use of R software to perform all the analyses in the book

- A new chapter on alternative methods for categorical data, including smoothing and regularization methods (such as the lasso), classification methods such as linear discriminant analysis and classification trees, and cluster analysis

- New sections in many chapters introducing the Bayesian approach for the methods of that chapter

- More than 70 analyses of data sets to illustrate application of the methods, and about 200 exercises, many containing other data sets

- An appendix showing how to use SAS, Stata, and SPSS, and an appendix with short solutions to most odd-numbered exercises

Written in an applied, nontechnical style, this book illustrates the methods using a wide variety of real data, including medical clinical trials, environmental questions, drug use by teenagers, horseshoe crab mating, basketball shooting, correlates of happiness, and much more.

An Introduction to Categorical Data Analysis, Third Edition is an invaluable tool for statisticians and biostatisticians as well as methodologists in the social and behavioral sciences, medicine and public health, marketing, education, and the biological and agricultural sciences.

商品描述(中文翻譯)

標準參考書籍的珍貴新版本

統計方法在類別數據中的使用顯著增加,特別是在生物醫學和社會科學的應用中。類別數據分析導論(第三版) 總結了這些方法,並展示了如何使用軟體來應用這些方法。讀者將會發現一種統一的廣義線性模型方法,將邏輯回歸和離散數據的對數線性模型與連續數據的常規回歸相連接。

新版本的價值增添包括:

- 使用 R 軟體執行書中所有分析的示例

- 一個關於類別數據替代方法的新章節,包括平滑和正則化方法(如套索)、分類方法如線性判別分析和分類樹,以及聚類分析

- 許多章節中新增的部分,介紹該章節方法的貝葉斯方法

- 超過 70 個數據集的分析,以說明這些方法的應用,並提供約 200 道練習題,許多包含其他數據集

- 附錄展示如何使用 SAS、Stata 和 SPSS,並附錄提供大多數奇數練習題的簡短解答

本書以應用的、非技術性的風格撰寫,使用各種真實數據來說明這些方法,包括醫療臨床試驗、環境問題、青少年藥物使用、鋼針蟹交配、籃球投籃、幸福感的相關因素等。

類別數據分析導論(第三版) 是統計學家、生物統計學家以及社會和行為科學、醫學和公共衛生、市場營銷、教育以及生物和農業科學中的方法學家的寶貴工具。

作者簡介

ALAN AGRESTI is Distinguished Professor Emeritus at the University of Florida. He has presented short courses on categorical data methods in 35 countries. He is the author of seven books, including the bestselling Categorical Data Analysis (Wiley), Foundations of Linear and Generalized Linear Models (Wiley), Statistics: The Art and Science of Learning from Data (Pearson), and Statistical Methods for the Social Sciences (Pearson).

作者簡介(中文翻譯)

阿蘭·阿格雷斯提是佛羅里達大學的榮譽特聘教授。他在35個國家舉辦過有關類別數據方法的短期課程。他是七本書的作者,包括暢銷書《類別數據分析》(Wiley)、《線性與廣義線性模型的基礎》(Wiley)、《統計學:從數據中學習的藝術與科學》(Pearson)以及《社會科學的統計方法》(Pearson)。

目錄大綱

1 Introduction
2 Analyzing Contingency Tables
3 Generalized Linear Models
4 Logistic Regression
5 Building and Applying Logistic Regression Models
6 Multicategory Logit Models
7 Loglinear Models for Contingency Tables and Counts
8 Models for Matched Pairs
9 Marginal Modeling of Correlated, Clustered Responses
10 Random Effects: Generalized Linear Mixed Models
11 Classification and Smoothing
12 A Historical Tour of Categorical Data Analysis
Appendix: Software for Categorical Data Analysis

Brief Solutions to Odd-Numbered Exercises
Bibliography
Examples Index
Subject Index

目錄大綱(中文翻譯)

1 Introduction

2 Analyzing Contingency Tables

3 Generalized Linear Models

4 Logistic Regression

5 Building and Applying Logistic Regression Models

6 Multicategory Logit Models

7 Loglinear Models for Contingency Tables and Counts

8 Models for Matched Pairs

9 Marginal Modeling of Correlated, Clustered Responses

10 Random Effects: Generalized Linear Mixed Models

11 Classification and Smoothing

12 A Historical Tour of Categorical Data Analysis

Appendix: Software for Categorical Data Analysis



Brief Solutions to Odd-Numbered Exercises

Bibliography

Examples Index

Subject Index