Multivariable Modeling and Multivariate Analysis for the Behavioral Sciences

Brian S. Everitt

September 28, 2009 by CRC Press
Textbook - 320 Pages - 113 B/W Illustrations
ISBN 9781439807699 - CAT# K10396
Series: Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences

USD$87.95

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Features

    • Presents an accessible introduction to intermediate statistics for behavioral scientists
    • Contains a large number of real data sets arising from actual problems, including cognitive behavioral therapy, crime rates, and drug usage
    • Separates mathematical details from the main body of the text
    • Removes the burden of performing necessary calculations by encouraging the use of R and providing the code online
    • Includes many real-world examples, graphs, and exercises
    • Provides solutions to the problems as well as all R code and data sets for the examples on the book’s website

    Summary

    Multivariable Modeling and Multivariate Analysis for the Behavioral Sciences shows students how to apply statistical methods to behavioral science data in a sensible manner. Assuming some familiarity with introductory statistics, the book analyzes a host of real-world data to provide useful answers to real-life issues.

    The author begins by exploring the types and design of behavioral studies. He also explains how models are used in the analysis of data. After describing graphical methods, such as scatterplot matrices, the text covers simple linear regression, locally weighted regression, multiple linear regression, regression diagnostics, the equivalence of regression and ANOVA, the generalized linear model, and logistic regression. The author then discusses aspects of survival analysis, linear mixed effects models for longitudinal data, and the analysis of multivariate data. He also shows how to carry out principal components, factor, and cluster analyses. The final chapter presents approaches to analyzing multivariate observations from several different populations.

    Through real-life applications of statistical methodology, this book elucidates the implications of behavioral science studies for statistical analysis. It equips behavioral science students with enough statistical tools to help them succeed later on in their careers. Solutions to the problems as well as all R code and data sets for the examples are available at www.crcpress.com

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