Shoukri, M. M.

Analysis of correlated data with SAS and R / Mohamed M. Shoukri , Mohammad A. Chaudhary. - 3rd ed. - Boca Raton : Chapman & Hall/CRC, c2007. - 295 p. : ill. ; 25 cm. +

Originally published: Statistical methods for health sciences. 2nd ed. Boca Raton, Fla. : CRC Press, c1999.

Includes bibliographical references (p. 283-289) and index.

PREFACE TO THE FIRST EDITION PREFACE TO THE SECOND EDITION PREFACE TO THE THIRD EDITION ANALYZING CLUSTERED DATA Regression Analysis for Clustered Data Generalized Linear Models Fitting Alternative Models for Clustered Data ANALYSIS OF CROSS-CLASSIFIED DATA Measures of Association in 2 x 2 Tables Analysis of Several 2 x 2 Contingency Tables Analysis of 1:1 Matched Pairs Statistical Analysis of Clustered Binary Data Sample Size Requirements for Clustered Binary Data Discussion MODELING BINARY OUTCOME DATA The Logistic Regression Model Modeling Correlated Binary Outcome Data Logistic Regression for Case-Control Studies Sample-Size Calculations for Logistic Regression ANALYSIS OF CLUSTERED COUNT DATA Poisson Regression Model Inference and Goodness of Fit Over-Dispersion in Count Data Count Data Random Effects Models Other Models ANALYSIS OF TIME SERIES Simple Descriptive Methods Fundamental Concepts in the Analysis of Time Series Models for Stationary Time Series ARIMA Models Forecasting Modeling Seasonality with ARIMA: The Condemnation Rates Series Revisited REPEATED MEASURES AND LONGITUDINAL DATA ANALYSIS Methods for the Analysis of Repeated Measures Data Mixed Linear Regression Models Examples Using the SAS Mixed and GLIMMIX Procedures SURVIVAL DATA ANALYSIS Examples Estimating the Survival Probabilities Modeling Correlated Survival Data Sample Size Requirements for Survival Data REFERENCES INDEX Introductions appear at the beginning of each chapter. Table of contents

Discusses the methodologies used for the analysis of clustered and correlated data. This work includes a chapter devoted to the modeling and analyzing of normally distributed variables under clustered sampling designs. It offers an analysis of correlated count data that focuses on over-dispersion



9781584886198 (acidfree paper) 1584886196 1584886196 (acidfree paper)

2007000593


Epidemiology--Statistical methods.

RA652.2.M3 / S53 2007

614.4 / SHA 2007

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