Applied Categorical and Count Data Analysis
暫譯: 應用類別與計數資料分析
Tang, Wan, He, Hua, Tu, Xin M.
- 出版商: CRC
- 出版日期: 2023-04-06
- 售價: $3,630
- 貴賓價: 9.5 折 $3,449
- 語言: 英文
- 頁數: 381
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 0367568276
- ISBN-13: 9780367568276
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相關分類:
Data Science
海外代購書籍(需單獨結帳)
商品描述
Developed from the authors' graduate-level biostatistics course, Applied Categorical and Count Data Analysis, Second Edition explains how to perform the statistical analysis of discrete data, including categorical and count outcomes. The authors have been teaching categorical data analysis courses at the University of Rochester and Tulane University for more than a decade. This book embodies their decade-long experience and insight in teaching and applying statistical models for categorical and count data. The authors describe the basic ideas underlying each concept, model, and approach to give readers a good grasp of the fundamentals of the methodology without relying on rigorous mathematical arguments.
The second edition covers classic concepts and popular topics, such as contingency tables, logistic regression models, and Poisson regression models, along with modern areas that include models for zero-modified count outcomes, parametric and semiparametric longitudinal data analysis, reliability analysis, and methods for dealing with missing values. As in the first edition, R, SAS, SPSS, and Stata programming codes are provided for all the examples, enabling readers to immediately experiment with the data in the examples and even adapt or extend the codes to fit data from their own studies.
Designed for a one-semester course for graduate and senior undergraduate students in biostatistics, this self-contained text is also suitable as a self-learning guide for biomedical and psychosocial researchers. It will help readers analyze data with discrete variables in a wide range of biomedical and psychosocial research fields.
Features:
-Describes the basic ideas underlying each concept and model.
-Includes R, SAS, SPSS and Stata programming codes for all the examples
-Features significantly expanded Chapters 4, 5, and 8 (Chapters 4-6, and 9 in the second edition.
-Expands discussion for subtle issues in longitudinal and clustered data analysis such as time varying covariates and comparison of generalized linear mixed-effect models with GEE.
商品描述(中文翻譯)
本書《應用類別與計數資料分析（第二版）》源自作者的研究生生物統計課程，解釋如何對離散數據進行統計分析，包括類別和計數結果。作者在羅徹斯特大學和杜蘭大學教授類別數據分析課程已超過十年。本書體現了他們在教授和應用類別及計數數據統計模型方面的十年經驗和見解。作者描述了每個概念、模型和方法背後的基本思想，使讀者能夠在不依賴嚴謹數學論證的情況下，充分掌握方法論的基本原理。
第二版涵蓋了經典概念和熱門主題，如列聯表、邏輯回歸模型和泊松回歸模型，以及現代領域，包括零修正計數結果的模型、參數和半參數的縱向數據分析、可靠性分析以及處理缺失值的方法。與第一版一樣，所有示例均提供 R、SAS、SPSS 和 Stata 的程式碼，讓讀者能立即對示例中的數據進行實驗，甚至可以調整或擴展程式碼以適應自己研究中的數據。
本書設計為一學期的研究生及高年級本科生生物統計課程，這本自成一體的教材也適合作為生物醫學和心理社會研究者的自學指南。它將幫助讀者分析在廣泛的生物醫學和心理社會研究領域中具有離散變數的數據。
特色：
- 描述每個概念和模型背後的基本思想。
- 包含所有示例的 R、SAS、SPSS 和 Stata 程式碼。
- 顯著擴展第 4、5 和 8 章（第二版中的第 4-6 章和第 9 章）。
- 擴展對縱向和聚類數據分析中微妙問題的討論，如時間變化的協變數以及比較廣義線性混合效應模型與 GEE。
作者簡介
Wan Tang (Ph.D.) is a Clinical Professor in the Department of Biostatistics and Data Science, Tulane University School of Public Health and Tropical Medicine. Dr. Tang's research interests include longitudinal data analysis, missing data modeling, structural equation models, causal inference, and nonparametric smoothing methods. He has co-edited a book on modern clinical trials.
Hua He (Ph.D.) is an Associate Professor in Biostatistics in the Department of Epidemiology at Tulane University School of Public Health and Tropical Medicine. Dr. He is a highly experienced biostatistician with expertise in longitudinal data analysis, structural equation models, potential outcome based causal inference, semiparametric models, ROC analysis and their applications to observational studies, and randomized controlled trials across a range of disciplines, especially in the behavioral and social sciences. She has co-authored a series of publications in peer-reviewed journals, one textbook on categorical data analysis and co-edited a book on statistical causal inference and their applications in public health research.
Xin Tu (Ph.D.) is a Professor in the Division of Biostatistics and Bioinformatics, Department of Family Medicine and Public Health, UCSD. Dr. Tu is well versed in statistical methods and their applications to a range of disciplines, particularly within the fields of biomedical, behavioral and social sciences. He has co-authored over 300 peer-reviewed publications, two textbooks on categorical data and applied U-statistics, and co-edited books on modern clinical trials and social network data analysis. He has done important work in the areas of longitudinal data analysis, causal inference, U-statistics, survival analysis with interval censoring and truncation, pooled testing, semiparametric efficiency, and has successfully applied his novel development to addressing important methodological problems in biomedical and psychosocial research.
作者簡介(中文翻譯)
唐萬 (Ph.D.) 是杜蘭大學公共衛生與熱帶醫學院生物統計與數據科學系的臨床教授。唐博士的研究興趣包括縱向數據分析、缺失數據建模、結構方程模型、因果推斷以及非參數平滑方法。他共同編輯了一本關於現代臨床試驗的書籍。
何華 (Ph.D.) 是杜蘭大學公共衛生與熱帶醫學院流行病學系的生物統計學副教授。何博士是一位經驗豐富的生物統計學家，專長於縱向數據分析、結構方程模型、基於潛在結果的因果推斷、半參數模型、ROC分析及其在觀察性研究和隨機對照試驗中的應用，特別是在行為科學和社會科學領域。她共同撰寫了一系列在同行評審期刊上發表的文章，一本關於類別數據分析的教科書，以及共同編輯了一本關於統計因果推斷及其在公共衛生研究中的應用的書籍。
涂欣 (Ph.D.) 是加州大學聖地牙哥分校家庭醫學與公共衛生系生物統計與生物資訊學部的教授。涂博士精通統計方法及其在多個學科中的應用，特別是在生物醫學、行為科學和社會科學領域。他共同撰寫了超過300篇同行評審的出版物，兩本關於類別數據和應用U統計的教科書，以及共同編輯了關於現代臨床試驗和社交網絡數據分析的書籍。他在縱向數據分析、因果推斷、U統計、帶間隔審查和截斷的生存分析、合併測試、半參數效率等領域做出了重要貢獻，並成功將其新穎的發展應用於解決生物醫學和心理社會研究中的重要方法論問題。
