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Growth Curve Models and Statistical Diagnostics - (Springer Statistics) by Jian-Xin Pan & Kai-Tai Fang (Hardcover)
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Highlights
- Growth curve models are an active research area in multivariate analysis with applications to economics, biology, medical research, and epidemiology.
- Author(s): Jian-Xin Pan & Kai-Tai Fang
- 388 Pages
- Mathematics, Probability & Statistics
- Series Name: Springer Statistics
Description
Book Synopsis
Growth curve models are an active research area in multivariate analysis with applications to economics, biology, medical research, and epidemiology. This monograph by two of the leading researchers in the area discusses both theoretical and practical aspects.Review Quotes
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)
