R Computing Environment

All of the programs provided on this page work in the R computing environment, which is available as a free download for PC or Mac.  Some basic information on getting started using R is provided in the User's Manual for the taxometric programs (below).

Taxometric Analysis

Taxometric Program Code.  This .R file contains the program code to perform taxometric analyses, along with a handful of related functions.  [January 9, 2012]

User's Manual.  This PDF file describes how to get started using R and then documents and illustrates the use of the taxometric programs and related functions.  [March 10, 2012]

R Workspace.  This .RData file contains the taxometric program code along with all of the data files that are shown and used in the User's Manual plus the 8 data sets that are analyzed throughout our taxometrics book (below).  [January 9, 2012.]

Taxometrics References.  This PDF file contains a bibliography on the taxometric method, including published studies that have used the method. (Please email me with corrections or updates.)  [February 16, 2012]

Generating Multivariate Nonnormal Data

This program code implements the methods described in:

Ruscio, J., & Kaczetow, W. (2008). Simulating multivariate nonnormal data using an iterative technique. Multivariate Behavioral Research, 43, 355-381. 

GenData Program.  This .R file contains the program code for use in R.  [November 17, 2009]

GenData Program.  This .txt file contains program code for use in SAS.  Dipl. Stat. (FH) Thomas Franke wrote the SAS code and graciously allowed me to provide it on this web site.  [November 11, 2009]

EFA with Comparison Data 

This program code implements the methods described in:

Ruscio, J., & Roche, B. (2012). Determining the number of factors to retain in an exploratory factor analysis using comparison data of known factorial structure. Psychological Assessment, 24, 282-292. 

EFA with Comparison Data.  This .R file contains the program code.  Note that it has been extended to allow the use of Spearman rank-order correlations, which can accommodate data that are ordinal and/or non-normally distributed.  [November 28, 2012]

Bootstrap CI for A 

This program code implements the methods described in:

Ruscio, J., & Mullen, T. (2012). Confidence intervals for the probability of superiority effect size measure and the area under a receiver operating characteristic curve . Multivariate Behavioral Research, 47, 201-223. 

Bootstrap CI for A.  This .R file contains the program code.  [November 4, 2011]

Generalizations of A

This program code implements the methods described in:

Ruscio, J., & Gera, B. L. (in press). Generalizations and extensions of the probability of superiority effect size estimator. Multivariate Behavioral Research. 

Generalizations of A.  This .R file contains the program code.  [September 7, 2012]

Citation-Based Indices

This program code implements the methods described in:

Ruscio, J., Seaman, F., D’Oriano, C., Stremlo, E., & Mahalchik, K. (2012). Measuring scholarly impact using modern citation-based indices. Measurement: Interdisciplinary Research and Perspectives, 10, 123-146.  

Citation-Based Indices.  This .R file contains the program code.  [February 19, 2013]

Taxometrics Book

Ruscio, J., Haslam, N., and Ruscio, A. M. (2006). Introduction to the taxometric method: A practical guide. Mahwah, NJ: Lawrence Erlbaum Associates.

Reviews:
 British Journal of Mathematical and Statistical Psychology
PsycCritiques

Available in hardcover, paperback, and Kindle editions.

Description 

Introduction to the Taxometric Method is a user-friendly, practical guide to taxometric research. Drawing from both classic and contemporary research, it provides a comprehensive introduction to the method. With helpful tools and guidance, the book is intended to teach those new to the method, as well as those already familiar with it, tips on how to conduct and evaluate taxometric investigations. The book covers a broad range of analytic techniques, describing their logic and implementation as well as what is known about their performance from systematic study.

The book opens with the background material essential to understanding the research problems that the taxometric method addresses. The authors then explain the data requirements of taxometric analysis, the logic of each procedure, factors that can influence results and lead to misinterpretations, suggestions for choosing the best procedures, and methodological safeguards to prevent erroneous conclusions. Illustrative examples of each procedure and consistency test demonstrate how to perform analyses and interpret results using a variety of data sets. A checklist of conceptual and methodological issues that should be addressed in any investigation is included. The accompanying CD provides a variety of programs for performing taxometric analyses along with simulations and analyses of data sets.

Introduction to the Taxometric Method is ideal for researchers and students conducting or evaluating taxometric studies in the social and behavioral sciences, especially those in clinical and personality psychology, as well as those in the physical sciences, education, biology, and beyond. The book also serves as a text for courses on this method, or as a supplement in psychological assessment, statistics, or research methods courses. Familiarity with taxometrics is not assumed.

Table of Contents

Preface

Part I: Introduction and Background

Introduction
Why Latent Structure Matters
The Classification Problem

Part II: Taxometric Method

Data Requirements for Taxometrics
Taxometric Procedures I: MAXSLOPE, MAMBAC, and L-Mode
Taxometric Procedures II: MAXCOV and MAXEIG
Consistency Tests
Interpretational Issues
A Taxometric Checklist

Part III: Applications and Future Directions

Applications of the Taxometric Method
The Future of Taxometrics

Appendix A: Simulating Taxonic and Dimensional Comparison Data

Appendix B: Estimating Latent Parameters and Classifying Cases Using MAXCOV

Appendix C: Estimating the Taxon Base Rate Using MAXEIG

References
Author Index
Subject Index

Quotes

"...It will become the obvious text for anyone wishing to learn about taxometrics...the authors are three of the most productive contributors to this literature..."
David K. Marcus, PhD, University of Southern Mississippi

"The Ruscios and Haslam are leaders in the field of applied taxometric research, producing much of the work over the past several years... The book promises to make a strong contribution to the field and would be an indispensible reference to investigators interested in conducting taxometric research."
Timothy A. Brown, PhD, Boston University

"...A necessary guide to people doing taxometric research... I would recommend it to students and/or colleagues."
David H. Gleaves, PhD, University of Canterbury