Growth Curve Models and Statistical Diagnostics / Edition 1

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"This book provides a comprehensive introduction to the theory of growth curve models with an emphasis on statistical diagnostics. A variety of issues relating to model development, estimation, inference, and diagnostics is addressed, and criteria for detecting outliers and influential observations are developed within likelihood and Bayesian frameworks." This book is intended for postgraduates and statisticians whose research involves longitudinal modelling, multivariate analysis, and statistical diagnostics. Scientists engaged in analyzing longitudinal and repeated measures data will also find the book useful. The authors provide a sound theoretical development of growth curve models but also emphasize their application by providing worked examples in each chapter. The book assumes a basic knowledge of matrix algebra and linear regression.
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Editorial Reviews

From the Publisher

From the reviews:

"The book is well written and contains a goodly number of real-data applications." ISI

Short Book Reviews, Vol.23/1, April 2003

"This book offers an extensive view of Growth Curve Models and a wide range of issues related with statistical diagnosis. … Each chapter ends with some bibliographical notes that inform the reader about historical sources as well as about recent developments. The bibliographic list is impressive! … the information given about Growth Curve Models and Statistical Diagnosis is excellent. The book is written very rigorously and precisely and I strongly recommend it for statisticians or for applied scientists with some mathematical and statistical background." (Prof. C. García-Olaverri, Kwantitatieve Methoden, Vol. 72B5, 2003)

"The authors have written a basic book on a well developed and important field in multivariate statistical analysis. It will undoubtedly serve as a reference in this field." (Arjun K. Gupta, Zentralblatt MATH, Vol. 1024, 2003)

"This book presents methods for analyzing repeated measures and longitudinal data using the growth curve models (GCMs), with specific focus on the generalized multivariate analysis of variance (GMANOVA) model. … For researchers, the book’s main strength is its level of detail. … Theoreticians in multivariate analysis will find this book to be a good reference for this particular GCM and multivariate regression diagnosis." (Andrew M. Kuhn, Technometrics, Vol. 45 (3), 2003)

"Models are discussed for data variously described as growth curves, longitudinal data, or multilevel data. The text supplements the growing number of references on techniques for longitudinal data by focusing on diagnostics for outliers and influential observations. … the book is well written and does contain a goodly number of real-data applications." (J. O. Ramsey, Short Book Reviews, Vol. 23 (1), 2003)

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Product Details

  • ISBN-13: 9781441928641
  • Publisher: Springer New York
  • Publication date: 10/9/2011
  • Series: Springer Series in Statistics
  • Edition description: Softcover reprint of the original 1st ed. 2002
  • Edition number: 1
  • Pages: 388
  • Product dimensions: 6.00 (w) x 9.10 (h) x 0.90 (d)

Table of Contents

• Generalized Least Square Estimation
• Maximum Likelihood Estimation
• Discordant Outlier and Influential Observation
• Likelihood-Based Local Influence
• Bayesian Influence Assessment
• Bayesian Local Influence

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