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The use of statistical methods for analyzing categorical data has increased dramatically, particularly in the biomedical, social sciences, and financial industries. Responding to new developments, this book offers a comprehensive treatment of the most important methods for categorical data analysis. Categorical Data Analysis, Third Edition summarizes the latest methods for univariate and correlated multivariate categorical responses. Readers will find a unified generalized linear models approach that connects logistic regression and Poisson and negative binomial loglinear models for discrete data with normal regression for continuous data. This edition also features: An emphasis on logistic and probit regression methods for binary, ordinal, and nominal responses for independent observations and for clustered data with marginal models and random effects models. Two new chapters on alternative methods for binary response data, including smoothing and regularization methods, classification methods such as linear discriminant analysis and classification trees, and cluster analysis. New sections introducing the Bayesian approach for methods in that chapter. More than 100 analyses of data sets and over 600 exercises. Notes at the end of each chapter that provide references to recent research and topics not covered in the text, linked to a bibliography of more than 1,200 sources. A supplementary website showing how to use R and SAS; for all examples in the text, with information also about SPSS and Stata and with exercise solutions. Categorical Data Analysis, Third Edition is an invaluable tool for statisticians and methodologists, such as biostatisticians and researchers in the social and behavioral sciences, medicine and public health, marketing, education, finance, biological and agricultural sciences, and industrial quality control.

A number of advances have taken place in panel data analysis during the pastthree decades and it continues to be one of the most active areas of research. This volume contains 13 significant contributions focusing on modelling strategies, data issues, theoretical analysis and applications. Applied econometrics papers on the economics of labor, health, telecommunications, finance and macroeconomics are provided as well as a survey of recent theoretical developments in panal data analysis. Contributors include both well known scholars and younger researchers from Australia, Canada, Europe and the United States of America

Longitudinal data analysis for biomedical and behavioral sciencesThis innovative book sets forth and describes methods for the analysis of longitudinaldata, emphasizing applications to problems in the biomedical and behavioral sciences. Reflecting the growing importance and use of longitudinal data across many areas of research, the text is designed to help users of statistics better analyze and understand this type of data

This pocket guide provides an in-depth introduction to 29 of the most widely used data sets in social work and the social sciences. Readers will find information about each data set, how to locate and use the data, what types of questions the data may answer, and the key variables in the data

Interpersonal phenomena such as attachment, conflict, person perception, helping, and influence have traditionally been studied by examining individuals in isolation, which falls short of capturing their truly interpersonal nature. This book offers state-of-the-art solutions to this age-old problem by presenting methodological and data-analytic approaches useful in investigating processes that take place among dyads: couples, coworkers, or parent-child, teacher-student, or doctor-patient pairs, to name just a few. Rich examples from psychology and across the behavioral and social sciences help