Linear Mixed Models: A Practical Guide Using Statistical Software, 3/e (Hardcover)
暫譯: 線性混合模型：使用統計軟體的實用指南，第3版 (精裝本)

高度推薦於 JASA、Technometrics 及其他領先的統計期刊，本暢銷書的前兩版展示了如何通過各種軟體輕鬆執行複雜的線性混合模型 (LMM) 分析。《線性混合模型：使用統計軟體的實用指南》第三版繼續逐步引導讀者進行 LMM 的擬合過程。

第三版提供了針對最新版本的 SAS、SPSS、R、Stata 和 HLM 擬合線性混合效應模型的可用工具的全面更新。所有範例均已更新，重點放在結果的可視化和解釋的新工具上。新增了混合效應建模的概念和理論發展，並新增了一章關於混合效應模型的效能分析。

**特色：**
- 專門 dedicates 一整章介紹 LMM 的關鍵理論，適用於聚類、縱向和重複測量數據
- 提供必要的軟體程式碼的描述、解釋和範例，以擬合 SAS、SPSS、R、Stata 和 HLM 中的 LMM
- 包含詳細的估計和結果表格，便於跨軟體程序進行比較
- 提供來自各種研究環境和研究設計的真實數據集的逐步分析，包括假設檢驗、結果解釋和模型診斷
- 在每章中整合軟體程式碼，以比較每個套件的相對優缺點
- 附有網站，提供軟體程式碼、數據集、附加文件和更新

本書非常適合任何使用軟體進行統計建模的人，通過在一本方便的指南中涵蓋最受歡迎的 LMM 擬合軟體，消除了閱讀多本特定於軟體的文本的需要。作者通過真實世界的範例來說明模型和方法，使讀者能夠比較不同軟體程序中的模型擬合選項和結果。

Brady T. West is a research professor in the Survey Methodology Program, located within the Survey Research Center at the Institute for Social Research (ISR) on the University of Michigan-Ann Arbor (U-M) campus. He earned his PhD from the Michigan Program in Survey and Data Science (formerly the Michigan Program in Survey Methodology) in 2011. Before that, he received an MA in Applied Statistics from the U-M Statistics Department in 2002, being recognized as an Outstanding First-year Applied Masters student, and a BS in Statistics with Highest Honors and Highest Distinction from the U-M Statistics Department in 2001. His current research interests include total survey error / total data quality, responsive and adaptive survey design, interviewer effects, survey paradata, the analysis of complex sample survey data, and multilevel regression models for clustered and longitudinal data. He has developed short courses on statistical analysis using SAS, SPSS, R, Stata, and HLM, and regularly consults on the use of procedures in these software packages for the analysis of longitudinal and clustered data. The author or co-author of more than 180 peer-reviewed publications and three edited volumes on survey methodology, he is also a co-author of a book entitled Applied Survey Data Analysis (with Steven Heeringa and Patricia Berglund), the second edition of which was published by Chapman Hall in 2017. He lives in Dexter, Michigan with his wife Laura, his son Carter, and his daughter Everleigh.

Kathy Welch is a retired former senior statistician and statistical software consultant at CSCAR (Consulting for Statistics, Computing & Analytics Research) at the University of Michigan, Ann Arbor. She received a B.A. in sociology (1969), an M.P.H. in epidemiology and health education (1975), and an M.S. in biostatistics (1984) from the University of Michigan (UM). During her career, she regularly consulted on the use of SAS, SPSS, Stata, and HLM for analysis of clustered and longitudinal data, taught a course on statistical software packages in the University of Michigan Department of Biostatistics, and taught short courses on SAS software. She also co-developed and co-taught a course on analysis of data from clustered and longitudinal studies at the School of Public Health at the University of Michigan.

Andrzej Galecki is a research professor in the Division of Geriatric Medicine, Department of Internal Medicine, and Institute of Gerontology at the University of Michigan Medical School, and in the Department of Biostatistics at the University of Michigan School of Public Health. He received a M.Sc. in applied mathematics (1977) from the Technical University of Warsaw, Poland, and an M.D. (1981) from the Medical Academy of Warsaw. In 1985 he earned a Ph.D. in epidemiology from the Institute of Mother and Child Care in Warsaw (Poland). Since 1990, Dr. Galecki has collaborated with researchers in gerontology and geriatrics. His research interests lie in the development and application of statistical methods for analyzing correlated and over-dispersed data. He developed the SAS macro NLMEM for nonlinear mixed-effects models, specified as a solution of ordinary differential equations. His research (Galecki, 1994) on a general class of covariance structures for two or more within-subject factors is considered to be one of the very first approaches to the joint modeling of multiple outcomes. Examples of these structures have been implemented in SAS proc mixed and the MIXED command in SPSS. In 2015 he was selected as a Fellow of the American Statistical Association. He is also a co-author of more than 120 publications.

Brenda Gillespie is the associate director of CSCAR (Consulting for Statistics, Computing & Analytics Research) and a research associate professor of Biostatistics at the University of Michigan, Ann Arbor. She received an A.B. in mathematics (1972) from Earlham College in Richmond, Indiana, an M.S. in statistics (1975) from The Ohio State University, and earned a Ph.D. in statistics (1989) from Temple University in Philadelphia, Pennsylvania. Dr. Gillespie has collaborated extensively with researchers in health-related fields, and has worked with mixed models as the primary statistician on the Collaborative Initial Glaucoma Treatment Study (CIGTS), the Dialysis Outcomes Practice Pattern Study (DOPPS), the Scientific Registry of Transplant Recipients (SRTR), the University of Michigan Dioxin Study, and at the Complementary and Alternative Medicine Research Center at the University of Michigan.

Brady T. West 是密西根大學安娜堡校區社會研究所（ISR）調查方法學計畫的研究教授。他於2011年獲得密西根調查與數據科學計畫（前身為密西根調查方法學計畫）的博士學位。在此之前，他於2002年獲得密西根大學統計系的應用統計碩士學位，並被認可為優秀的第一年應用碩士生，於2001年獲得密西根大學統計系的最高榮譽和最高成就的統計學學士學位。他目前的研究興趣包括總調查誤差/總數據質量、響應式和自適應調查設計、訪談者效應、調查輔助數據、複雜樣本調查數據的分析，以及針對聚類和縱向數據的多層次回歸模型。他開發了使用SAS、SPSS、R、Stata和HLM進行統計分析的短期課程，並定期就這些軟體包中程序的使用提供諮詢，以分析縱向和聚類數據。他是超過180篇同行評審出版物和三本調查方法學編輯卷的作者或合著者，並且是一本名為《應用調查數據分析》（與Steven Heeringa和Patricia Berglund合著）的書的合著者，該書的第二版於2017年由Chapman Hall出版。他與妻子Laura、兒子Carter和女兒Everleigh住在密西根州Dexter。

Kathy Welch 是密西根大學安娜堡校區CSCAR（統計、計算與分析研究諮詢）的退休前高級統計師和統計軟體顧問。她於1969年獲得社會學學士學位（B.A.），於1975年獲得流行病學和健康教育碩士學位（M.P.H.），以及於1984年獲得生物統計學碩士學位（M.S.）均來自密西根大學。在她的職業生涯中，她定期就使用SAS、SPSS、Stata和HLM進行聚類和縱向數據分析提供諮詢，並在密西根大學生物統計系教授統計軟體包課程，還教授SAS軟體的短期課程。她還共同開發並共同教授了一門關於聚類和縱向研究數據分析的課程，該課程在密西根大學公共衛生學院開設。

Andrzej Galecki 是密西根大學醫學院老年醫學部、內科系及老年學研究所的研究教授，以及密西根大學公共衛生學院生物統計系的教授。他於1977年獲得波蘭華沙科技大學的應用數學碩士學位（M.Sc.），並於1981年獲得華沙醫學院的醫學博士學位（M.D.）。他於1985年在波蘭華沙母嬰保健研究所獲得流行病學博士學位（Ph.D.）。自1990年以來，Galecki博士與老年學和老年醫學的研究人員合作。他的研究興趣在於開發和應用統計方法來分析相關和過度分散的數據。他開發了SAS宏NLMEM，用於非線性混合效應模型，該模型被指定為常微分方程的解。他的研究（Galecki, 1994）關於兩個或多個受試者內因素的一般協方差結構類別被認為是多重結果聯合建模的最早方法之一。這些結構的例子已在SAS proc mixed和SPSS的MIXED命令中實現。2015年，他被選為美國統計協會的會士。他也是超過120篇出版物的合著者。

Brenda Gillespie 是密西根大學安娜堡校區CSCAR（統計、計算與分析研究）的副主任及生物統計學研究副教授。她於1972年在印第安納州的Earlham College獲得數學學士學位（A.B.），於1975年在俄亥俄州立大學獲得統計碩士學位（M.S.），並於1989年在賓夕法尼亞州的天普大學獲得統計博士學位（Ph.D.）。Gillespie博士與健康相關領域的研究人員廣泛合作，並在合作初期青光眼治療研究（CIGTS）、透析結果實踐模式研究（DOPPS）、科學移植受者登記（SRTR）、密西根大學二噁英研究以及密西根大學互補與替代醫學研究中心擔任主要統計師，使用混合模型進行研究。