縱向數(shù)據(jù)分析方法與應(yīng)用（英文版）

定　價：￥89.00

作　者：	劉憲著
出版社：	高等教育出版社
叢編項：	應(yīng)用統(tǒng)計學(xué)叢書
標(biāo)　簽：	暫缺

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ISBN：	9787040436884	出版時間：	2015-10-01	包裝：	平裝
開本：	16開	頁數(shù)：	511	字數(shù)：

內(nèi)容簡介

　　《縱向數(shù)據(jù)分析方法與應(yīng)用（英文版）》旨在系統(tǒng)地介紹縱向數(shù)據(jù)分析的基本概念、理論設(shè)定和應(yīng)用步驟，重點通過SAS計算機程序?qū)嶋H數(shù)據(jù)進行分析，從而深入淺出地描述縱向數(shù)據(jù)分析的各類模型。書中涉及的統(tǒng)計方法包括各類描述性估算法、線性混合效應(yīng)模型、隨機效應(yīng)的統(tǒng)計推斷及估計、殘差協(xié)方差結(jié)構(gòu)類型、廣義線性混合效應(yīng)模型的理論性描述、二分組結(jié)局混合效應(yīng)模型、多結(jié)局混合效應(yīng)模型、各類潛變量發(fā)展模型、缺損數(shù)據(jù)分類及分析方法以及一些縱向分析方面的專題研究?！犊v向數(shù)據(jù)分析方法與應(yīng)用（英文版）》著重于各類縱向分析模型的實際運用，而不拘泥于模型的純理論推論，從而使對縱向數(shù)據(jù)分析有興趣的科研人員以及大學(xué)生、研究生從中受益。

作者簡介

　　劉憲，密歇根大學(xué)社會學(xué)博士（1991）?，F(xiàn)任美國國防醫(yī)科大學(xué)（Uniformed Services University of the Health Sciences）精神病學(xué)系教授、高級研究員及美國沃特·里德國家軍事醫(yī)學(xué)中心（Walter Reed National Military Medical Center）研究員、高級統(tǒng)計師。著有專著《生存分析：模型與應(yīng)用》及《縱向數(shù)據(jù)分析方法與應(yīng)用》。所發(fā)表論文與著作在國際上被大量引用。曾多次獲得美國國立衛(wèi)生研究院（National Institutes of Health）、退伍軍人事務(wù)部及密歇根大學(xué)研究基金。主要研究領(lǐng)域為縱向數(shù)據(jù)分析、生存分析與死亡率交叉研究、老年人口學(xué)、創(chuàng)傷事件與精神疾病。

圖書目錄

Biography
Preface
CHAPTER 1 Intr0dueti0n
1．1 What is Longitudinal Data Analysis?
1．2 History of Longitudinal Analysis and its Progress
1．3 Longitudinal Data Structures
1．3．1 Multivariate Data Structure
1．3．2 Univariate Data Structure
1．3．3 Balanced and Unbalanced Longitudinal Data
1．4 Missing Data Patterns and Mechanisms
1．5 Sources of Correlation in Longitudinal Processes
1．6 Time Scale and the Number of Time Points
1．7 Basic Expressions of Longitudinal Modeling
1．8 Organization of the Book and Data Used for Illustrations
1．8．1 Randomized Controlled Clinical Trial on the Effectiveness of Acupuncture Treatment on PTSD
1．8．2 Asset and Health Dynamics Among the Oldest Old （AHEAD）
CHAPTER 2 Traditional Methods of Longitudinal Data Analysis．．
2．1 Descriptive Approaches
2．1．1 Time Plots of Trends
2．1．2 Paired t-Test
2．1．3 Effect Size Between Two Means and its Confidence Interval
2．1．4 Empirical Illustration： Descriptive Analysis on the Effectiveness of Acupuncture Treatment in Reduction of PTSD Symptom Severity
2．2 Repeated Measures ANOVA
2．2．1 Specifications of One-Factor ANOVA
2．2．2 One-Factor Repeated Measures ANOVA
2．2．3 Specifications of Two-Factor Repeated Measures ANOVA
2．2．4 Empirical Illustration： A Two-Factor Repeated Measures ANOVA - The Effectiveness of Acupuncture Treatment on PCL Revisited
2．3 Repeated Measures MANOVA
2．3．1 General MANOVA
2．3．2 Hypothesis Testing on Effects in MANOVA
2．3．3 Repeated Measures MANOVA
2．3．4 Empirical Illustration： A Two-Factor Repeated Measures MANOVA on the Effectiveness of Acupuncture Treatment on Two Psychiatric Disorders
2．4 Summary
CHAPTER 3 Linear Mixed-Effects Models
3．1 Introduction of Linear Mixed Models： Three Cases
3．1．1 Case I： One-Factor Linear Mixed Model with Random Intercept
3．1．2 Case II： linear Mixed Model with Random Intercept and Random Slope
3．1．3 Case III： Linear Mixed Model with Random Effects and Three Covariates
3．2 Formalization of Linear Mixed Models
3．2．1 General Specification of Linear Mixed Models
3．2．2 Variance-Covariance Matrix and Intraindividual Correlation
3．2．3 Formalization of Variance-Covariance Components
3．3 Inference and Estimation of Fixed Effects In Linear
Mixed Models
3．3．1 Maximum Likelihood Methods
3．3．2 Statistical Inference and Hypothesis Testing on Fixed Effects
3．3．3 Missing Data
3．4 Trend Analysis
3．4．1 Polynomial Time Functins
3．4．2 Methods to Reduce Collinearity in Polynomial Time Terms
3．4．3 Numeric Checks on Polynomial Time Functions
3．5 Empirical Illustrations： Application of Two Linear
Mixed Models
3．5．1 Linear Mixed Model on Effectiveness of Acupuncture Treatment on PCL Score
3．5．2 Linear Mixed Model on Marital Status and Disability Severity in Older Americans
3．6 Summary
……
CHAPTER 4 Restricted Maximum Likelihood and Inference of Random Effects in Linear Mixed Models
CHAPTER 5 Patterns of Residual Covariance Structure
CHAPTER 6 Residual and Influence Diagnostics
CHAPTER 7 Special Topics on Linear Mixed Models
CHAPTER 8 Generalized Linear Mixed Models on Nonlinear Longitudinal Data
CHAPTER 9 Generalized Estimating Equations （GEEs） Models．
CHAPTER 10 Mixed-Effects Regression Model for Binary Longitudinal Data
CHAPTER 11 Mixed-Effects Multinomial Logit Model for Nominal Outcomes
CHAPTER 12 Longitudinal Transition Models for Categorical Response Data
CHAPTER 13 Latent Growth， Latent Growth Mixture， and Group-Based Models
CHAPTER 14 Methods for Handling Missing Data
Appendix A Orthogonal Polynomials
Appendix B The Delta Method
Appendix C Quasi-Likelihood Functions and Properties
Appendix D Model Specification and SAS Program for Random Coefficient Multinomial Logit Model on Health State Among Older Americans
References
Subject Index