Modern Psychometrics With R

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.

Today psychometrics plays an increasingly important role in all our lives as testing and assessment occurs from preschool until retirement. This book introduces the reader to the subject in all its aspects, ranging from its early history, school examinations, how to construct your own test, controversies about IQ and recent developments in testing on the internet. In Part one of Modern Psychometrics, Rust and Golombok outline the history of the field and discuss central theoretical issues such as IQ, personality and integrity testing and the impact of computer technology and the internet. In Part two a practical step-by-step guide to the development of a psychometric test is provided. This will enable anyone wishing to develop their own test to plan, design, construct and validate it to a professional standard. This third edition has been extensively updated and expanded to take into account recent developments in the field, making it the ideal companion for those studying for the British Psychological Society’s Certificates of Competence in Testing. Modern Psychometrics combines an up to date scientific approach to the subject with a full consideration of the political and ethical issues involved in the large scale implementation of psychometrics testing in today’s highly networked society, particularly in terms of issues of diversity and internationalism. It will be useful to students and practictioners at all levels who are interested in psychometrics.

Currently there are many introductory textbooks on educational measurement and psychometrics as well as R. However, there is no single book that covers important topics in measurement and psychometrics as well as their applications in R. The Handbook of Educational Measurement and Psychometrics Using R covers a variety of topics, including classical test theory; generalizability theory; the factor analytic approach in measurement; unidimensional, multidimensional, and explanatory item response modeling; test equating; visualizing measurement models; measurement invariance; and differential item functioning. This handbook is intended for undergraduate and graduate students, researchers, and practitioners as a complementary book to a theory-based introductory or advanced textbook in measurement. Practitioners and researchers who are familiar with the measurement models but need to refresh their memory and learn how to apply the measurement models in R, would find this handbook quite fulfilling. Students taking a course on measurement and psychometrics will find this handbook helpful in applying the methods they are learning in class. In addition, instructors teaching educational measurement and psychometrics will find our handbook as a useful supplement for their course.

"This popular text introduces the reader to all aspects of psychometric assessment, including its history, how to construct and administer traditional tests and the latest techniques for psychometric assessment online. Rust, Kosinski and Stillwell begin with a comprehensive introduction to the increased sophistication in psychometric methods and regulation that took place during the 20th century, including the many benefits to governments, businesses and customers. In this new edition, the authors explore the increasing influence of the internet wherein everything we do online is available for psychometric analysis, often by AI systems operating at scale and in real time. The intended and unintended consequences of this paradigm shift are examined in detail, and key controversies, such as privacy and the psychographic microtargeting of online messages, are addressed. Furthermore, this new edition includes brand new chapters on Item Response Theory and Computer-Adaptive Testing, Test Equating and Differential Item Functioning, and Using R in psychometric settings. Modern Psychometrics combines an up to date scientific approach with full consideration of the political and ethical issues involved in the implementation of psychometrics testing in today's society. It will be invaluable to both undergraduate and postgraduate students as well as practitioners who are seeking an introduction to modern psychometric methods"--

The edition of this classic text has been completely revised and updated, taking into account recent developments in the field of psychometrics. Part 1 of Modern Psychometrics outlines the background, history and controversies surrounding psychological testing. Part 2 provides a practical guide for developing a psychometric test. Modern Psychometrics forms the ideal companion for those studying for the British Psychological Society's Certificates of Competence in Testing

A systematic, innovative introduction to the field of network analysis, Network Psychometrics with R: A Guide for Behavioral and Social Scientists provides a comprehensive overview of and guide to both the theoretical foundations of network psychometrics as well as modelling techniques developed from this perspective. Written by pioneers in the field, this textbook showcases cutting-edge methods in an easily accessible format, accompanied by problem sets and code. After working through this book, readers will be able to understand the theoretical foundations behind network modelling, infer network topology, and estimate network parameters from different sources of data. This book features an introduction on the statistical programming language R that guides readers on how to analyse network structures and their stability using R. While Network Psychometrics with R is written in the context of social and behavioral science, the methods introduced in this book are widely applicable to data sets from related fields of study. Additionally, while the text is written in a non-technical manner, technical content is highlighted in textboxes for the interested reader. Network Psychometrics with R is ideal for instructors and students of undergraduate and graduate level courses and workshops in the field of network psychometrics as well as established researchers looking to master new methods. This book is accompanied by a companion website with resources for both students and lecturers.

Applying Contemporary Statistical Techniques explains why traditional statistical methods are often inadequate or outdated when applied to modern problems. Wilcox demonstrates how new and more powerful techniques address these problems far more effectively, making these modern robust methods understandable, practical, and easily accessible. Highlights: * Assumes no previous training in statistics * Explains when and why modern methods provide more accurate results * Provides simple descriptions of when and why conventional methods can be highly unsatisfactory * Covers the latest developments on multiple comparisons * Includes recent advances in risk-based methods * Features many illustrations and examples using data from real studies * Describes and illustrates easy-to-use s-plus functions for applying cutting-edge techniques "The book is quite unique in that it offers a lot of up-to-date statistical tools. No other book at this level comes close in this aspect." Xuming He -University of Illinois, Urbana

This introduction to R for students of psychology and health sciences aims to fast-track the reader through some of the most difficult aspects of learning to do data analysis and statistics. It demonstrates the benefits for reproducibility and reliability of using a programming language over commercial software packages such as SPSS. The early chapters build at a gentle pace, to give the reader confidence in moving from a point-and-click software environment, to the more robust and reliable world of statistical coding. This is a thoroughly modern and up-to-date approach using RStudio and the tidyverse. A range of R packages relevant to psychological research are discussed in detail. A great deal of research in the health sciences concerns questionnaire data, which may require recoding, aggregation and transformation before quantitative techniques and statistical analysis can be applied. R offers many useful and transparent functions to process data and check psychometric properties. These are illustrated in detail, along with a wide range of tools R affords for data visualisation. Many introductory statistics books for the health sciences rely on toy examples - in contrast, this book benefits from utilising open datasets from published psychological studies, to both motivate and demonstrate the transition from data manipulation and analysis to published report. R Markdown is becoming the preferred method for communicating in the open science community. This book also covers the detail of how to integrate the use of R Markdown documents into the research workflow and how to use these in preparing manuscripts for publication, adhering to the latest APA style guidelines.