Abstract
With the advent of the free statistical language R, several item response theory (IRT) programs have been introduced as psychometric packages in R. These R programs have an advantage of a free open source over commercial software. However, in research and practical settings, the quality of results produced by free programs may be called into questions. The aim of this study is to provide information regarding the performance of those free R IRT software for the recovery item parameters and their standard errors. The study conducts a series of comparisons via simulations for popular unidimensional IRT models: the Rasch, 2-parameter logistic, 3-parameter logistic, generalized partial credit, and graded response models. The R IRT programs included in the present study are “eRm,” “ltm,” “mirt,” “sirt,” and “TAM.” This study also reports convergence rates reported by both “eRm” and “ltm” and the elapsed times for the estimation of the models under different simulation conditions.
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Notes
- 1.
Note that this study used the latest version of each package available at the time of study: “eRm” (0.15–6; November 12, 2015), “ltm” (1.0–0; December 20, 2013), “TAM” (1.15–0; December 15, 2015), “sirt” (1.8–9; June 28, 2015), and “mirt” (1.15; January 21, 2016).
- 2.
Note that “mirt” uses actually “+ intercept” but for consistency with the “ltm” expression, “–intercept” was used in this article.
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Kim, T., Paek, I. (2017). A Comparison of Item Parameter and Standard Error Recovery Across Different R Packages for Popular Unidimensional IRT Models. In: van der Ark, L.A., Wiberg, M., Culpepper, S.A., Douglas, J.A., Wang, WC. (eds) Quantitative Psychology. IMPS 2016. Springer Proceedings in Mathematics & Statistics, vol 196. Springer, Cham. https://doi.org/10.1007/978-3-319-56294-0_36
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