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This book is concerned with the use of generalized linear models for univariate and multivariate regression analysis. It deals with regression analysis in a wide sense to include not only cross-sectional analysis but also time series and longitudinal data. The authors provide a detailed introductory survey of the subject based on the analysis of real data drawn from a variety of subjects including the biological sciences, economics, and the social sciences. Where possible, technical details and proofs are deferred to an appendix in order to provide an accessible account for non-experts. After a review of generalized linear models, topics covered include: models for multi-categorical responses, this is ideally suited for applied statisticians, graduate students of statistics, and students and researchers with a strong interest in statistics and data analysis from areas of econometrics, biometrics, and social sciences.

Multivariate Statistical Modelling Based On Generalized Linear Models

Introduction * Modelling and Analysis of Cross-sectional Data: A Review of Univariate Generalized Linear Models * Models for Multicategorical Responses: Multivariate Extensions of Generalized Linear Models * Selecting and Checking Models * Semi- and Nonparametric Approaches to Regression Analysis * Fixed Parameter Models for Time Series and Longitual Data * Random Effects Models * State Space and Hidden Markov Models * Survival Models