Quantitative methods programs are provided in a single .zip file, with the contents described below. Files ending with YYYY-MM-DD indicate the date of the latest update. References appear at the bottom of this page.
As of May 30, 2017, the program code to perform taxometric analyses that was previously available via this web site has been replaced with the RTaxometrics package (Ruscio & Wang, 2017). More information is available here.
Generating Multivariate Nonnormal Data
GenData and FactorAnalysis.R – Program code to implement the methods described in Ruscio and Kaczetow (2008).
GenData for SAS.txt – Program code for use in SAS. Dipl. Stat. (FH) Thomas Franke wrote the SAS code and graciously allowed me to provide it here.
EFA with Comparison Data
EFA Comparison Data.R – Program code to implement the methods described in Ruscio and Roche (2012). The code has been extended to allow the use of Spearman rank-order correlations, which can accommodate data that are ordinal and/or non-normally distributed.
Bootstrap CI for A
Bootstrap CI for A.R – Program code to implement the methods described in Ruscio and Mullen (2012).
Generalizations of A
A.R – Program code to implement the methods described in Ruscio & Gera (2013).
Metrics.R – Program code to implement the methods described in Ruscio, Seaman, D’Oriano, Stremlo, and Mahalchik (2012).
Adjusting Scores.xlsx – Excel file to implement the methods described in Kuhlthau, Ruscio, Bastedo, & Furey (2017).
Kuhlthau, K., Ruscio, J., Bastedo, C., & Furey, M. (2017). What’s in a grade? A professor’s guide to adjusting scores. Journal on Excellence in College Teaching, 28, 81-110.
Ruscio, J., & Gera, B. L. (2013). Generalizations and extensions of the probability of superiority effect size estimator. Multivariate Behavioral Research, 48, 208-219.
Ruscio, J. Haslam, N., & Ruscio, A. M. (2006). Introduction to the taxometric method: A practical guide. Mahwah, NJ: Lawrence Erlbaum Associates.
Ruscio, J., & Kaczetow, W. (2008). Simulating multivariate nonnormal data using an iterative technique. Multivariate Behavioral Research, 43, 355-381.
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.
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.
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.
Ruscio, J., & Wang, S. B. (2017). RTaxometrics: Taxometric analysis. R package version 2.0. Available at https://CRAN.R-project.org/package=RTaxometrics.