
Statistical Methods for the Analysis of Repeated Measurements
By: Charles S. Davis
Hardcover | 6 November 2003
At a Glance
444 Pages
24.13 x 15.88 x 2.54
Hardcover
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Industry Reviews
From the reviews:
MATHEMATICAL REVIEWS
"...the book covers a wide range of topics, including inference based on normal theory, repeated categorical outcomes and missing values. The book is based on lecture notes used by the author since 1991. Hence, the material and the structure of the book have been well tested by different audiences. Another feature of the book is the inclusion of a very rich collection of problems with excellent real data. Thus, it is a nice textbook for a semester course on repeated measurements and longitudinal data."
SHORT BOOK REVIEW
"Each major topic is introduced logically; background theory is clearly elucidated, and at least one example is carefully worked in detail. The use of eighty real sets of data, given in full, is a most attractive feature. Attention is concentrated on those techniques that are most readily available in software. ... This should prove to be a very useful text for teacher, student and practitioner alike."
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
"Most other books on repeated measurements tend to focus on specialized topics. In my opinion, [this] book is the most comprehensive and readable of the lot. I would highly recommend its use as a text for a semester-length graduate course for biostatistics and statistics students and also as resource book for consulting biostatisticians and statisticians. In addition, this book would be a valuable resource for students from other fields of study (e.g., the health sciences) who have a statistical aptitude. The book is definitely worth the price."
"The intention of the book is 'to provide a reasonably comprehensive overview of methods for the analysis of repeated measurements' with focus on standard statistical methods ... . In my opinion the book gives a nice, comprehensive overview of methods for the analysis of repeated measurements. ... The availability of data sets, overheads, etc. is a very valuable supplement for both teachers and students. ... The book ... could be a natural choice for a course in repeated measurements for graduate students in (bio-) statistics." (Niels Trolle Andersen, Statistics in Medicine, Vol. 24 (5), 2005)
"This book is a very interesting and comprehensive summary of a wide selection of statistical methods for the analysis of repeated measurements. It is indeed an ideal and carefully written text to be used as a reference guide for practitioners and, in addition, as a great, up to date and very complete textbook for a graduate-level course in Statistics and/or Biostatistics. ... I highly recommend Statistical Methods ... as a good reference book for anyone interested in looking into the different available methodologies ... ." (Vicente Nunez-Anton, Journal of Applied Statistics, Vol. 30 (10), December, 2003)
"This book provides a comprehensive introduction to a wide variety of statistical methods for the analysis of repeated measurements. ... In conclusion, as acourse text on repeated measurements this book clearly has major strengths over others in that it provides coverage on a wide range of topics and provides extensive further reading material. ... I would recommend this text as a general reference book on repeated measurements which would make a worthwhile addition to a departmental library." (Fiona Holland, Pharmaceutical Statistics, 2003)
"Most other books on repeated measurements ... tend to focus on specialized topics. In my opinion, Statistical Methods for the Analysis of Repeated Measurements book is the most comprehensive and readable of the lot. I would highly recommend its use as a text for a semester-length graduate course for biostatistics and statistics students and ... for consulting biostatisticians and statisticians. ... a valuable resource for students from other fields of study ... who have a statistical aptitude. The book is definitely worth the price." (Melvin L. Moeschberger, Journal of the American Statistical Association, March, 2003)
"The book aims at describing, discussing and demonstrating a variety of statistical methods for the analysis of repeated measurements ... . the book covers a very wide range of topics, including inference based on normal theory, repeated categorical outcomes and missing values. ... Another feature of the book is the inclusion of a very rich collection of problems with excellent real data. Thus, it is a nice textbook for a semester course on repeated measurements and longitudinal data." (Jack C. Lee, Mathematical Reviews, 2003 e)
"This book is intended to provide a comprehensive introduction to a wide range of statistical methods for the analysis of repeated measurements. ... For use in a course, I would use it for an applied graduate-level statistics course on linear models for analysis of repeated measurements. This text is useful not only with regards to the statistical methods, but also for the real data examples that can be explored with the various modelsand methods under study." (James R. Kenyon, Technometrics, Vol. 45 (1), 2003)
"This book provides a reasonably comprehensive overview of a wide variety of statistical methods for the analysis of repeated measurements ... . The important features of this book include a summary of both classical and recent methods for continuous and categorical outcome variables, numerous homework problems, and the extensive use of real data sets in examples. ... This book will be of interest to graduate students in statistics and biostatistics as well as to practicing statisticians in academic, industry and research institutions." (Ivan Krivy, Zentralblatt MATH, Vol. 985, 2002)
| p. v | |
| Introduction | p. 1 |
| Repeated Measurements | p. 1 |
| Advantages and Disadvantages of Repeated Measurements Designs | p. 2 |
| Notation for Repeated Measurements | p. 3 |
| Missing Data | p. 4 |
| Sample Size Estimation | p. 8 |
| Outline of Topics | p. 9 |
| Choosing the ""Best"" Method of Analysis | p. 12 |
| Univariate Methods | p. 15 |
| Introduction | p. 15 |
| One Sample | p. 16 |
| Multiple Samples | p. 21 |
| Comments | p. 26 |
| Problems | p. 28 |
| Normal-Theory Methods: Unstructured Multivariate Approach | p. 45 |
| Introduction | p. 45 |
| Multivariate Normal Distribution Theory | p. 46 |
| The Multivariate Normal Distribution | p. 46 |
| The Wishart Distribution | p. 46 |
| Wishart Matrices | p. 47 |
| Hotelling's T2 Statistic | p. 47 |
| Hypothesis Tests | p. 48 |
| One-Sample Repeated Measurements | p. 49 |
| Methodology | p. 49 |
| Examples | p. 50 |
| Comments | p. 54 |
| Two-Sample Repeated Measurements | p. 55 |
| Methodology | p. 55 |
| Example | p. 57 |
| Comments | p. 60 |
| Problems | p. 61 |
| Normal-Theory Methods: Multivariate Analysis of Variance | p. 73 |
| Introduction | p. 73 |
| The Multivariate General Linear Model | p. 74 |
| Notation and Assumptions | p. 74 |
| Parameter Estimation | p. 75 |
| Hypothesis Testing | p. 76 |
| Comparisons of Test Statistics | p. 77 |
| Profile Analysis | p. 78 |
| Methodology | p. 78 |
| Example | p. 81 |
| Growth Curve Analysis | p. 83 |
| Introduction | p. 83 |
| The Growth Curve Model | p. 83 |
| Examples | p. 87 |
| Problems | p. 94 |
| Normal-Theory Methods: Repeated Measures ANOVA | p. 103 |
| Introduction | p. 103 |
| The Fundamental Model | p. 104 |
| One Sample | p. 106 |
| Repeated Measures ANOVA Model | p. 106 |
| Sphericity Condition | p. 109 |
| Example | p. 111 |
| Multiple Samples | p. 112 |
| Repeated Measures ANOVA Model | p. 112 |
| Example | p. 115 |
| Problems | p. 116 |
| Normal-Theory Methods: Linear Mixed Models | p. 125 |
| Introduction | p. 125 |
| The Linear Mixed Model | p. 126 |
| The Usual Linear Model | p. 126 |
| The Mixed Model | p. 126 |
| Parameter Estimation | p. 127 |
| Background on REML Estimation | p. 128 |
| Application to Repeated Measurements | p. 130 |
| Examples | p. 134 |
| Two Groups, Four Time Points, No Missing Data | p. 134 |
| Three Groups, 24 Time Points, No Missing Data | p. 139 |
| Four Groups, Unequally Spaced Repeated Measurements, Time-Dependent Covariate | p. 145 |
| Comments | p. 149 |
| Use of the Random Intercept and Slope Model | p. 149 |
| Effects of Choice of Covariance Structure on Estimates and Tests | p. 151 |
| Performance of Linear Mixed Model Test Statistics and Estimators | p. 155 |
| Problems | p. 156 |
| Weighted Least Squares Analysis of Repeated Categorical Outcomes | p. 169 |
| Introduction | p. 169 |
| Background | p. 170 |
| The Multinomial Distribution | p. 170 |
| Linear Models Using Weighted Least Squares | p. 171 |
| Analysis of Categorical Data Using Weighted Least Squares | p. 175 |
| Taylor Series Variance Approximations for Nonlinear Response Functions | p. 178 |
| Application to Repeated Measurements | p. 184 |
| Overview | p. 184 |
| One Population, Dichotomous Response, Repeated Measurements Factor Is Unordered | p. 184 |
| One Population, Dichotomous Response, Repeated Measurements Factor Is Ordered | p. 187 |
| One Population, Polytomous Response | p. 191 |
| Multiple Populations, Dichotomous Response | p. 196 |
| Accommodation of Missing Data | p. 204 |
| Overview | p. 204 |
| Ratio Estimation for Proportions | p. 204 |
| One Population, Dichotomous Response | p. 205 |
| Multiple Populations, Dichotomous Response | p. 209 |
| Assessing the Missing-Data Mechanism | p. 214 |
| Problems | p. 220 |
| Randomization Model Methods for One-Sample Repeated Measurements | p. 239 |
| Introduction | p. 239 |
| The Hypergeometric Distribution and Large-Sample Tests of Randomness for 2 × 2 Tables | p. 240 |
| The Hypergeometric Distribution | p. 240 |
| Test of Randomness for a 2 × 2 Contingency Table | p. 241 |
| Test of Randomness for s 2 × 2 Contingency Tables | p. 242 |
| Application to Repeated Measurements: Binary Response, Two Time Points | p. 244 |
| The Multiple Hypergeometric Distribution and Large-Sample Tests of Randomness for r × c Tables | p. 246 |
| The Multiple Hypergeometric Distribution | p. 247 |
| Test of Randomness for an r × c Contingency Table | p. 248 |
| Test of Randomness for s r × c Tables | p. 249 |
| Cochran-Mantel-Haenszel Mean Score Statistic | p. 251 |
| Cochran-Mantel-Haenszel Correlation Statistic | p. 253 |
| Application to Repeated Measurements: Polytomous Response, Multiple Time Points | p. 253 |
| Introduction | p. 253 |
| The General Association Statistic QG | p. 255 |
| The Mean Score Statistic QM and the Correlation Statistic Qc | p. 255 |
| Accommodation of Missing Data | p. 258 |
| General Association Statistic QG | p. 258 |
| Mean Score Statistic QM | p. 260 |
| Correlation Statistic QC | p. 262 |
| Use of Mean Score and Correlation Statistics for Continuous Data | p. 263 |
| Problems | p. 264 |
| Methods Based on Extensions of Generalized Linear Models | p. 273 |
| Introduction | p. 273 |
| Univariate Generalized Linear Models | p. 274 |
| Introduction | p. 274 |
| Random Component | p. 275 |
| Systematic Component | p. 279 |
| Link Function | p. 279 |
| Canonical Links | p. 279 |
| Parameter Estimation | p. 281 |
| Quasilikelihood | p. 286 |
| Introduction | p. 286 |
| Construction of a Quasilikelihood Function | p. 287 |
| Quasilikelihood Estimating Equations | p. 289 |
| Comparison Between Quasilikelihood and Generalized Linear Models | p. 291 |
| Overview of Methods for the Analysis of Repeated Measurements | p. 291 |
| Introduction | p. 291 |
| Marginal Models | p. 292 |
| Random-Effects Models | p. 293 |
| Transition Models | p. 293 |
| Comparisons of the Three Approaches | p. 294 |
| The GEE Method | p. 295 |
| Introduction | p. 295 |
| Methodology | p. 296 |
| Example | p. 301 |
| Hypothesis Tests Using Wald Statistics | p. 308 |
| Assessing Model Adequacy | p. 309 |
| Sample Size Estimation | p. 310 |
| Studies of the Properties of GEE | p. 311 |
| Computer Software | p. 312 |
| Cautions Concerning the Use of GEE | p. 313 |
| Subsequent Developments | p. 314 |
| Alternative Procedures for Estimation of GEE Association Parameters | p. 314 |
| Other Developments and Extensions | p. 316 |
| GEE1 and GEE2 | p. 316 |
| Extended Generalized Estimating Equations (EGEE) | p. 317 |
| Likelihood-Based Approaches | p. 318 |
| Random-Effects Models | p. 318 |
| Methods for the Analysis of Ordered Categorical Repeated Measurements | p. 320 |
| Introduction | p. 320 |
| Univariate Cumulative Logit Models for Ordered Categorical Outcomes | p. 321 |
| The Univariate Proportional-Odds Model | p. 322 |
| The Stram-Wei-Ware Methodology for the Analysis of Ordered Categorical Repeated Measurements | p. 324 |
| Extension of GEE to Ordered Categorical Outcomes | p. 331 |
| Problems | p. 332 |
| Nonparametric Methods | p. 347 |
| Introduction | p. 347 |
| Overview | p. 348 |
| Multivariate One-Sample and Multisample Tests for Complete Data | p. 350 |
| One Sample | p. 350 |
| Multiple Samples | p. 350 |
| Two-Sample Tests for Incomplete Data | p. 355 |
| Introduction | p. 355 |
| The Wei-Lachin Method | p. 355 |
| The Wei-Johnson Method | p. 356 |
| Examples | p. 362 |
| Problems | p. 364 |
| Table of Contents provided by Publisher. All Rights Reserved. |
ISBN: 9780387953700
ISBN-10: 0387953701
Series: Springer Texts in Statistics
Published: 6th November 2003
Format: Hardcover
Language: English
Number of Pages: 444
Audience: Professional and Scholarly
Publisher: Springer Nature B.V.
Country of Publication: US
Dimensions (cm): 24.13 x 15.88 x 2.54
Weight (kg): 0.72
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