Variance Components
Mixed Models, Methodologies and Applications
1st Edition
Published on 1. June 1997
Book
Hardback
350 pages
978-0-412-72860-0 (ISBN)
Description
Variance Components Estimation deals with the evaluation of the variation between observable data or classes of data. This is an up-to-date, comprehensive work that is both theoretical and applied. Topics include ML and REML methods of estimation; Steepest-Acent, Newton-Raphson, scoring, and EM algorithms; MINQUE and MIVQUE, confidence intervals for variance components and their ratios; Bayesian approaches and hierarchical models; mixed models for longitudinal data; repeated measures and multivariate observations; as well as non-linear and generalized linear models with random effects.
Reviews / Votes
"This is an intermediate level monograph on variance component estimation. It is concise and well written... I recommend this book to any practicing statistician or researcher. It could also be used to supplement an intermediate or advanced course on linear models, analysis of variance, or variance components."-Technometrics, February 2002
More details
Series
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Professional and scholarly
Professional
Dimensions
Height: 229 mm
Width: 152 mm
Weight
342 gr
ISBN-13
978-0-412-72860-0 (9780412728600)
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Schweitzer Classification
Persons
Content
The Study of Variation. One-Way Classification. Two-Way Cross-Classification. Randomized Blocks. BIBDs and Latin Squares. Nested Classifications. Maximum Likelihood Estimation. The MINQUE and MIVQUE. Non-Negative Estimation of Variance Components. Confidence Intervals. Genetic and Environmental Effects.