LEADER 05636nam 2200757 450 001 9910555092603321 005 20221021141047.0 010 $a9781119513469 010 $a1-119-51346-4 010 $a1-118-55179-6 024 7 $a10.1002/9781119513469 035 $a(CKB)2670000000269723 035 $a(EBL)1051443 035 $a(OCoLC)823236113 035 $a(SSID)ssj0000754603 035 $a(PQKBManifestationID)12278998 035 $a(PQKBTitleCode)TC0000754603 035 $a(PQKBWorkID)10716544 035 $a(PQKB)10871782 035 $a(MiAaPQ)EBC1051443 035 $a(PPN)263076598 035 $a(EXLCZ)992670000000269723 100 $a20110322h20112011 uy| 0 101 0 $aeng 135 $aurbn#|||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aApplied longitudinal analysis /$fGarrett M. Fitzmaurice, Nan M. Laird, James H. Ware 205 $a2nd ed. 210 1$aHoboken, New Jersey :$cWiley,$d[2011] 210 4$dİ2011 215 $a1 online resource (1309 p.) 225 1 $aWiley series in probability and statistics 300 $aDescription based upon print version of record. 311 08$a0-470-38027-6 320 $aIncludes bibliographical references (pages 671-693) and index. 327 $aCover; Half Title page; Title page; Copyright page; Dedication; Preface; Preface to First Edition; Acknowledgments; Part I: Introduction to Longitudinal and Clustered Data; Chapter 1: Longitudinal and Clustered Data; 1.1 Introduction; 1.2 Longitudinal and Clustered Data; 1.3 Examples; 1.4 Regression Models for Correlated Responses; 1.5 Organization of the Book; 1.6 Further Reading; Chapter 2: Longitudinal Data: Basic Concepts; 2.1 Introduction; 2.2 Objectives of Longitudinal Analysis; 2.3 Defining Features of Longitudinal Data; 2.4 Example: Treatment of Lead-Exposed Children Trial 327 $a2.5 Sources of Correlation in Longitudinal Data2.6 Further Reading; Part II: Linear Models for Longitudinal Continuous Data; Chapter 3: Overview of Linear Models for Longitudinal Data; 3.1 Introduction; 3.2 Notation and Distributional Assumptions; 3.3 Simple Descriptive Methods of Analysis; 3.4 Modeling the Mean; 3.5 Modeling the Covariance; 3.6 Historical Approaches; 3.7 Further Reading; Chapter 4: Estimation and Statistical Inference; 4.1 Introduction; 4.2 Estimation: Maximum Likelihood; 4.3 Missing Data Issues; 4.4 Statistical Inference; 4.5 Restricted Maximum Likelihood (REML) Estimation 327 $a4.6 Further ReadingChapter 5: Modeling the Mean: Analyzing Response Profiles; 5.1 Introduction; 5.2 Hypotheses Concerning Response Profiles; 5.3 General Linear Model Formulation; 5.4 Case Study; 5.5 One-Degree-of-Freedom Tests for Group by Time Interaction; 5.6 Adjustment for Baseline Response; 5.7 Alternative Methods of Adjusting for Baseline Response; 5.8 Strengths and Weaknesses of Analyzing Response Profiles; 5.9 Computing: Analyzing Response Profiles Using PROC MIXED in SAS; 5.10 Further Reading; Chapter 6: Modeling the Mean: Parametric Curves; 6.1 Introduction 327 $a6.2 Polynomial Trends in Time6.3 Linear Splines; 6.4 General Linear Model Formulation; 6.5 Case Studies; 6.6 Computing: Fitting Parametric Curves Using PROC MIXED in SAS; 6.7 Further Reading; Chapter 7: Modeling the Covariance; 7.1 Introduction; 7.2 Implications of Correlation among Longitudinal Data; 7.3 Unstructured Covariance; 7.4 Covariance Pattern Models; 7.5 Choice among Covariance Pattern Models; 7.6 Case Study; 7.7 Discussion: Strengths and Weaknesses of Covariance Pattern Models; 7.8 Computing: Fitting Covariance Pattern Models Using PROC MIXED in SAS; 7.9 Further Reading 327 $aChapter 8: Linear Mixed Effects Models8.1 Introduction; 8.2 Linear Mixed Effects Models; 8.3 Random Effects Covariance Structure; 8.4 Two-Stage Random Effects Formulation; 8.5 Choice among Random Effects Covariance Models; 8.6 Prediction of Random Effects; 8.7 Prediction and Shrinkage; 8.8 Case Studies; 8.9 Computing: Fitting Linear Mixed Effects Models Using PROC MIXED in SAS; 8.10 Further Reading; Chapter 9: Fixed Effects versus Random Effects Models; 9.1 Introduction; 9.2 Linear Fixed Effects Models; 9.3 Fixed Effects versus Random Effects: Bias-Variance Trade-off 327 $a9.4 Resolving the Dilemma of Choosing Between Fixed and Random Effects Models 330 $a"Since the publication of the first edition, the authors have solicited feedback from both the instructors who use the book as a text for their courses as well as the researchers who use the book as a resource for their research. Thus, the improved Second Edition of Applied Longitudinal Analysis features many additions and revisions based on the feedback of readers, making it the go-to reference for applied use in public health, epidemiology, and pharmaceutical sciences"--$cProvided by publisher. 410 0$aWiley series in probability and statistics. 606 $aLongitudinal method 606 $aRegression analysis 606 $aMultivariate analysis 606 $aMedical statistics 615 0$aLongitudinal method. 615 0$aRegression analysis. 615 0$aMultivariate analysis. 615 0$aMedical statistics. 676 $a519.5/3 676 $a519.53 686 $aMAT029000$2bisacsh 700 $aFitzmaurice$b Garrett M.$f1962-$01218768 702 $aLaird$b Nan M.$f1943- 702 $aWare$b James H.$f1941- 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910555092603321 996 $aApplied longitudinal analysis$92818354 997 $aUNINA