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Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences

Series Editor: Jeff Gill, Steven G. Heeringa, J. Scott Long, Thomas A.B. Snijders, Wim J Van Der Linden

New and Published Books

11-18 of 18 results in Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences
  1. Applied Survey Data Analysis

    By Steven G. Heeringa, Brady T. West, Patricia A. Berglund

    Series: Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences

    Taking a practical approach that draws on the authors’ extensive teaching, consulting, and research experiences, Applied Survey Data Analysis provides an intermediate-level statistical overview of the analysis of complex sample survey data. It emphasizes methods and worked examples using available...

    Published April 4th 2010 by Chapman and Hall/CRC

  2. Multivariable Modeling and Multivariate Analysis for the Behavioral Sciences

    By Brian S. Everitt

    Series: Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences

    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...

    Published September 27th 2009 by CRC Press

  3. Foundations of Factor Analysis, Second Edition

    By Stanley A Mulaik

    Series: Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences

    Providing a practical, thorough understanding of how factor analysis works, Foundations of Factor Analysis, Second Edition discusses the assumptions underlying the equations and procedures of this method. It also explains the options in commercial computer programs for performing factor analysis...

    Published September 24th 2009 by Chapman and Hall/CRC

  4. Linear Causal Modeling with Structural Equations

    By Stanley A. Mulaik

    Series: Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences

    Emphasizing causation as a functional relationship between variables that describe objects, Linear Causal Modeling with Structural Equations integrates a general philosophical theory of causation with structural equation modeling (SEM) that concerns the special case of linear causal relations. In...

    Published June 15th 2009 by Chapman and Hall/CRC

  5. Analysis of Multivariate Social Science Data, Second Edition

    By David J. Bartholomew, Fiona Steele, Jane Galbraith, Irini Moustaki

    Series: Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences

    Drawing on the authors’ varied experiences working and teaching in the field, Analysis of Multivariate Social Science Data, Second Editionenables a basic understanding of how to use key multivariate methods in the social sciences. With updates in every chapter, this edition expands its topics to...

    Published June 3rd 2008 by Chapman and Hall/CRC

  6. Bayesian Methods

    A Social and Behavioral Sciences Approach, Second Edition

    By Jeff Gill

    Series: Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences

    The first edition of Bayesian Methods: A Social and Behavioral Sciences Approach helped pave the way for Bayesian approaches to become more prominent in social science methodology. While the focus remains on practical modeling and basic theory as well as on intuitive explanations and derivations...

    Published November 25th 2007 by Chapman and Hall/CRC

  7. Statistical Test Theory for the Behavioral Sciences

    By Dato N. M. de Gruijter, Leo J. Th. van der Kamp

    Series: Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences

    Since the development of the first intelligence test in the early 20th century, educational and psychological tests have become important measurement techniques to quantify human behavior. Focusing on this ubiquitous yet fruitful area of research, Statistical Test Theory for the Behavioral Sciences...

    Published August 30th 2007 by Chapman and Hall/CRC

  8. Multiple Correspondence Analysis and Related Methods

    Edited by Michael Greenacre, Jorg Blasius

    Series: Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences

    As a generalization of simple correspondence analysis, multiple correspondence analysis (MCA) is a powerful technique for handling larger, more complex datasets, including the high-dimensional categorical data often encountered in the social sciences, marketing, health economics, and biomedical...

    Published June 22nd 2006 by Chapman and Hall/CRC