Modern Psychometrics with R

Author:   Patrick Mair
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2018
ISBN:  

9783319931753


Pages:   458
Publication Date:   27 September 2018
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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Modern Psychometrics with R


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Overview

This textbook describes the broadening methodology spectrum of psychological measurement in order to meet the statistical needs of a modern psychologist. The way statistics is used, and maybe even perceived, in psychology has drastically changed over the last few years; computationally as well as methodologically.  R has taken the field of psychology by storm, to the point that it can now safely be considered the lingua franca for statistical data analysis in psychology. The goal of this book is to give the reader a starting point when analyzing data using a particular method, including advanced versions, and to hopefully motivate him or her to delve deeper into additional literature on the method.   Beginning with one of the oldest psychometric model formulations, the true score model, Mair devotes the early chapters to exploring confirmatory factor analysis, modern test theory, and a sequence of multivariate exploratory method. Subsequent chapters present special techniques useful for modern psychological applications including correlation networks, sophisticated parametric clustering techniques, longitudinal measurements on a single participant, and functional magnetic resonance imaging (fMRI) data. In addition to using real-life data sets to demonstrate each method, the book also reports each method in three parts-- first describing when and why to apply it, then how to compute the method in R, and finally how to present, visualize, and interpret the results. Requiring a basic knowledge of statistical methods and R software, but written in a casual tone, this text is ideal for graduate students in psychology.  Relevant courses include methods of scaling, latent variable modeling, psychometrics for graduate students in Psychology, and multivariate methods in the social sciences.

Full Product Details

Author:   Patrick Mair
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2018
Weight:   0.718kg
ISBN:  

9783319931753


ISBN 10:   331993175
Pages:   458
Publication Date:   27 September 2018
Audience:   College/higher education ,  Postgraduate, Research & Scholarly
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Classical Test Theory.-Factor Analysis.- Path Analysis and Structural Equation Models.- Item Response Theory.- Preference Modeling.- Principal Component Analysis and Extensions.- Correspondence Analysis.- Gifi Methods.- Multidimensional Scaling.- Biplots.- Networks.- Parametric Cluster Analysis and Mixture Regression.- Modeling Trajectories and Time Series.- Analysis of fMRI Data.

Reviews

“The book gives an exhaustive overview of statistical methods that may be used when analyzing results of research in psychology. Main accent is on the use of R software during analysis of data. The main goal of the book is to provide the reader with main methods used for data analysis and how those methods may be executed using software package R.” (Jonas Šiaulys, zbMath 1414.62006, 2019)


The book gives an exhaustive overview of statistical methods that may be used when analyzing results of research in psychology. Main accent is on the use of R software during analysis of data. The main goal of the book is to provide the reader with main methods used for data analysis and how those methods may be executed using software package R. (Jonas Siaulys, zbMath 1414.62006, 2019)


Author Information

Patrick Mair is Senior Lecturer in Statistics in the Department of Psychology at Harvard University. His research focuses on computational and applied statistics with special emphasis on psychometric methods, such as latent variable models and multivariate exploratory techniques. Mair holds a doctorate in Statistics and a master’s degree in Psychology from the University of Vienna. He was also a Research Fellow at the Department of Statistics at the University of California, Los Angeles. 

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