Applying Generalized Linear Models
Applying Generalized Linear Models describes how generalized linear modelling procedures can be used for statistical modelling in many different fields, without becoming lost in problems of statistical inference. Many students, even in relatively advanced
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Springer
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Stephen Fienberg
Ingram Olkin
Springer Texts in Statistics Alfred: Elements of Statistics for the Life and Social Sciences Berger: An Introduction to Probability and Stochastic Processes Bilodeau and Brenner: Theory of Multivariate Statistics Blom: Probability and Statistics: Theory and Applications Brockwell and Davis: An Introduction to Times Series and Forecasting Chow and Teicher: Probability Theory: Independence, Interchangeability, Martingales, Third Edition Christensen: Plane Answers to Complex Questions: The Theory of Linear Models, Second Edition Christensen: Linear Models for Multivariate, Time Series, and Spatial Data Christensen: Log-Linear Models and Logistic Regression, Second Edition Creighton: A First Course in Probability Models and Statistical Inference Dean and Voss: Design and Analysis of Experiments du Toit, Steyn, and Stumpf: Graphical Exploratory Data Analysis Durrett: Essentials of Stochastic Processes Edwards: Introduction to Graphical Modelling Finkelstein and Levin: Statistics for Lawyers Flury: A First Course in Multivariate Statistics Jobson: Applied Multivariate Data Analysis, Volume I: Regression and Experimental Design Jobson: Applied Multivariate Data Analysis, Volume II: Categorical and Multivariate Methods Kalbfleisch: Probability and Statistical Inference, Volume I: Probability, Second Edition Kalbfleisch: Probability and Statistical Inference, Volume II: Statistical Inference, Second Edition Karr: Probability Keyfitz: Applied Mathematical Demography, Second Edition Kiefer: Introduction to Statistical Inference Kokoska and Nevison: Statistical Tables and Formulae Kulkarni: Modeling, Analysis, Design, and Control of Stochastic Systems Lehmann: Elements of Large-Sample Theory Lehmann: Testing Statistical Hypotheses, Second Edition Lehmann and Casella: Theory of Point Estimation, Second Edition Lindman: Analysis of Variance in Experimental Design Lindsey: Applying Generalized Linear Models Madansky: Prescriptions for Working Statisticians McPherson: Statistics in Scientific Investigation: Its Basis, Application, and Interpretation Mueller: Basic Principles of Structural Equation Modeling: An Introduction to LISREL and EQS (continued after index)
James K. Lindsey
Applying Generalized Linear Models With 35 Illustrations
Springer
James K. Lindsey Department of Biostatistics Limburgs Universitair Centrum 3590 Diepenbeek Belgium Editorial
Board
George Casella Biometrics Unit Cornell University Ithaca, NY 14853 USA
Stephen Fienberg Department of Statistics Camegie Mellon University Pittsburgh, PA 15213 USA
Ingram Olkin Department of Statistics Stanford University Stanford, CA 94305 USA
Library of Congress Cataloging-in-Publication Data Lindsey, James K. Applying generalized linear models / J.K. Lindsey p. cm. — (Springer texts in statistics) Includes bibliographical references (p. - ) and index. ISBN 0-387-98218-3 (hardcover: alk. paper) 1. Linear models (Statistics) I. Title. II. Se
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