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This volume describes how to conceptualize, perform, and critique traditional generalized linear models (GLMs) from a Bayesian perspective and how to use modern computational methods to summarize inferences using simulation. Introducing dynamic modeling for GLMs and containing over 1000 references and equations, Generalized Linear Models considers parametric and semiparametric approaches to overdispersed GLMs, presents methods of analyzing correlated binary data using latent variables. It also p...

This is the first text for those seeking appropriate statistical approaches to research data that is devoted entirely to the topic of contrasts. Contrast analysis permits us to ask more focused questions of our data. In return for a small amount of simple computation, we get very much greater statistical power, and can make very much clearer substantive interpretations of our research results. Contrast analysis should be employed in the context of the analysis of variance whenever the numerator...

Papers included in this volume deal with discriminant analysis, clustering techniques and software, multidimensional scaling, statistical, linguistic and artificial intelligence models and methods for pattern recognition and some of their applications. Further examined are the selection of subsets of variables for allocation and discrimination, and reviews of some paradoxes and open questions in the areas of variable selection, dimensionality, sample size and error estimation.

Praise for the First Edition "...[this book] should be on the shelf of everyone interested in ...longitudinal data analysis." Journal of the American Statistical Association Features newly developed topics and applications of the analysis of longitudinal data Applied Longitudinal Analysis, Second Edition presents modern methods for analyzing data from longitudinal studies and now features the latest state-of-the-art techniques. The book emphasizes practical, rather than theoretical, aspects of m...

Sample surveys form the most widely used method of collecting quantitative social data and offer extensive opportunities for analyzing social phenomena. However, the direct application of standard methods of statistical analysis, devised historically within different traditions of data collection such as experimentation, may be inappropriate and misleading. This volume discusses appropriate principles and methods for the analysis of surveys, such as stratified multi-stage sampling, as well as th...

After Karl Joreskog's first presentation in 1970, Structural Equation Modelling or SEM has become a main statistical tool in many fields of science. It is the standard approach of factor analytic and causal modelling in such diverse fields as sociology, education, psychology, economics, management and medical sciences. In addition to an extension of its application area, Structural Equation Modelling also features a continual renewal and extension of its theoretical background. The sixteen contr...

Although factorial analysis is widely used in the social sciences, there is some confusion as to how to use the techniqueÆs most powerful featureùthe evaluation of interaction effects. Written to remedy this situation, author James Jaccard clearly describes the issues underlying the effective analysis of interaction in factorial designs. The book begins by describing different ways of characterizing interactions in ANOVA, elucidating both moderator conceptualizations of interactions as well as t...

This book collects together 45 papers covering various aspects of the analysis of multiway data arrays. Mathematical properties of three-way and multiway arrays are investigated and their utilization for the statistical interpretation of complex data sets is emphasized. The volume is divided into 5 chapters. A specific introduction to each chapter has been prepared by the Editorial Board. Different methods of analysis are considered including: longitudinal and multimode factor analysis, generali...

Procrustean methods are used to transform one set of data to represent another set of data as closely as possible. The name derives from the Greek myth where Procrustes invited passers-by in for a pleasant meal and a night's rest on a magical bed that would exactly fit any guest. He then either stretched the guest on the rack or cut off their legs to make them fit perfectly into the bed. Theseus turned the tables on Procrustes, fatally adjusting him to fit his own bed. This text, the first mono...

Continuous Multivariate Distributions, Volume 1, Second Edition provides a remarkably comprehensive, self-contained resource for this critical statistical area. It covers all significant advances that have occurred in the field over the past quarter century in the theory, methodology, inferential procedures, computational and simulational aspects, and applications of continuous multivariate distributions. In-depth coverage includes MV systems of distributions, MV normal, MV exponential, MV extre...

Researchers involved in the collection of scientific data often end up with multivariate systems. When several variables are simultaneously measured on the same experimental unity, they are usually correlated, and the pattern formed is often too difficult for the human mind to grasp. This text discusses in detail many proven techniques for finding the dimensionality of the pattern and unravelling the information contained in the complexity of variables. The book includes exercises and solutions...

In this monograph, the author presents univariate and multivariate probabilistic inequalities with coverage on basic probabilistic entities like expectation, variance, moment generating function and covariance. These are built on the recent classical form of real analysis inequalities which are also discussed in full details. This treatise is the culmination and crystallization of the author's last two decades of research work in related discipline. Each of the chapters is self-contained and a f...

Presents different approaches to discrimination and classification problems from a statistical perspective. Provides computer projects concentrating on the most widely used and important algorithms, numerical examples, and theoretical questions reinforce to further develop the ideas introduced in the text.

AN UPDATED GUIDE TO STATISTICAL MODELING TECHNIQUES USED IN THE SOCIAL AND NATURAL SCIENCES This revised and updated second edition of Applied Univariate, Bivariate, and Multivariate Statistics: Understanding Statistics for Social and Natural Scientists, with Applications in SPSS and R contains an accessible introduction to statistical modeling techniques commonly used in the social and natural sciences. The text offers a blend of statistical theory and methodology and reviews both the technical...

The primary focus here is on log-linear models for contingency tables, but in this second edition, greater emphasis has been placed on logistic regression. The book explores topics such as logistic discrimination and generalised linear models, and builds upon the relationships between these basic models for continuous data and the analogous log-linear and logistic regression models for discrete data. It also carefully examines the differences in model interpretations and evaluations that occur d...