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Correlated Data Analysis: Modeling, Analytics, And Applications (Springer Series In Statistics)

This book covers recent developments in correlated data analysis. It utilizes the class of dispersion models as marginal components in the formulation of joint models for correlated data. This enables the book to cover a broader range of data types than the traditional generalized linear models. The reader is provided with a systematic treatment for the topic of estimating functions, and both gene...

Series: Springer Series in Statistics
Hardcover: 352 pages
Publisher: Springer; 2007 edition (July 27, 2007)
Language: English
ISBN-10: 9780387713922
ISBN-13: 978-0387713922
ASIN: 0387713921
Product Dimensions: 6.1 x 0.8 x 9.2 inches
Amazon Rank: 3219856
Format: PDF ePub djvu book

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“this is a great book with the specific information about correlated data analysis and longitudinal analysis. my professor recommended that too....”

alized estimating equations (GEE) and quadratic inference functions (QIF) are studied as special cases. In addition to the discussions on marginal models and mixed-effects models, this book covers new topics on joint regression analysis based on Gaussian copulas.