Programs

Most of my quantitative methods programs are now available as R packages, with some additional programs provided on this page. References appear below.

Taxometric Analysis

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

Program code to implement the methods described in Ruscio and Kaczetow (2008) is provided in the RGenData package.

Dipl. Stat. (FH) Thomas Franke wrote SAS code and graciously allowed me to provide it here.

EFA with Comparison Data 

Program code to implement the methods described in Ruscio and Roche (2012a) is provided in the RGenData package. 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 

Program code to implement the methods described in Ruscio and Mullen (2012) is provided in the RProbSup package.

Generalizations of A

Program code to implement the methods described in Ruscio & Gera (2013) is provided in the RProbSup package.

Citation-Based Indices

Program code to implement the methods described in Ruscio, Seaman, D’Oriano, Stremlo, and Mahalchik (2012) is provided in the RImpact package.

Standardized Variance Heterogeneity

Program code to implement the methods described in Ruscio and Roche (2012b) is available here.

Adjusting Scores

Program code to implement the methods described in Kuhlthau, Ruscio, Bastedo, & Furey (2017) is available here.

References

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. (2012a). 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., & Roche, B. (2012b). Variance heterogeneity in published psychological research: A review and a new index. Methodology, 8, 1-11.

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.