The SAGE Handbook of Quantitative Methods in Psychology

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Overview

Quantitative Psychology is arguably one of the oldest disciplines within the field of psychology and nearly all psychologists are exposed to quantitative psychology in some form. While textbooks in statistics, research methods, and psychological measurement exist none offer a unified treatment of quantitative psychology. The SAGE Handbook of Quantitative Methods in Psychology does just that. Each chapter covers a methodological topic with equal attention paid to established theory and the challenges facing methodologists as they address new research questions using that particular methodology. The reader will come away from each chapter with a greater understanding of the methodology being addressed as well as an understanding of the directions for future developments within that methodological area.

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Product Details

  • ISBN-13: 9781412930918
  • Publisher: SAGE Publications
  • Publication date: 8/22/2009
  • Edition description: New Edition
  • Pages: 800
  • Product dimensions: 7.10 (w) x 9.80 (h) x 2.00 (d)

Meet the Author

Dr. Maydeu-Olivares has been Assistant Professor of Statistics and Econometrics at the Universidad Carlos III, Professor of Marketing and Quantativative Methods at the IE Business School, and he is currently ICREA-Academia Distinguished Professor of Psychology at the University of Barcelona. Among other awards he has received the American Psychological Association (div 5) Dissertation Award, the Young Investigator (Cattell) Award from the Society of Multivariate Experimental Psychology, and the Catalan Young Investigator Award. He has published over 70 refereed articles and edited two volumes: Contemporary Psychometrics (2005) and Handbook of Quantitative Methods in Psychology (2009). He is currently President-Elect of the Psychometric Society.

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Table of Contents

PART ONE: DESIGN AND INFERENCE
Causal Inference in Randomized and Non-randomized Studies - Michael Sobel
The Definition, Identification and Estimation of Causal Parameters
Experimental Design - Roger Kirk
Quasi-Experimental Design - Charles Reichardt
Missing Data - Paul Allison
PART TWO: MEASUREMENT THEORY
Classical Test Theory - James Algina and Randall D Penfield
Factor Analysis - Robert C Mac Callum
Item Response Theory - David Thissen and Lynne Steinberg
Special Topics in Item Response Theory - Michael Edwards and Maria Orlando Edelen
Latent Class Analysis - David Rindskopf
PART THREE: SCALING
Multidimensional Scaling - Yoshio Takane et al
Correspondence Analysis, Multiple Correspondence Analysis and Recent Developments - Heungsun Hwang et al
Modeling Preference Data - Albert Maydeu-Olivares and Ulf B[um]ockenholt
PART FOUR: DATA ANALYSIS
Applications of Multiple Regression in Psychological Research - Razia Azen and David Budescu
Categorical Data Analysis with a Psychometric Twist - Carolyn Anderson
Multilevel Analysis - Jee-Seon Kim
An Overview and Some Contemporary Issues
Resampling Methods - William H Beasley and Joseph L Rodgers
Robust Data Analysis - Rand R Wilcox
Meta-Analysis - Andy Field
Bayesian Data Analysis - Herbert Hoijtink
Cluster Analysis - Lawrence Hubert et al
A Toolbox for MATLAB
PART FIVE: STRUCTURAL EQUATION MODELS
General SEM - Robert Cudeck
Maximum Likelihood And Bayesian Estimation For Nonlinear Structural Equation Models - Melanie Wall
Structural Equation Mixture Modeling - Conor Dolan
Multilevel Latent Variable Modeling - David Kaplan et al
Current Research and Recent Developments
PART SIX: LONGITUDINAL MODELS
Modeling Individual Change over Time - Suzanne Graham, Judy Singer and John Willett
Time Series Models for Examining Psychological Processes - Emilio Ferrer and Guangjian Zhang
Applications and New Developments
Event History Analysis - Jeroen Vermunt
PART SEVEN: SPECIALIZED METHODS
Neuroimaging Analysis (I) - Josep Marco-Pallarés et al
Electroencephalography
Neuroimaging Analysis (II) - Estela Camara et al
Magnetic Resonance Imaging
Functional Data Analysis - James O Ramsay

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