The R Journal: accepted article

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mudfold: An R Package for Nonparametric IRT Modelling of Unfolding Processes PDF download
Spyros E. Balafas, Wim P. Krijnen, Wendy J. Post and Ernst C. Wit

Abstract Item response theory (IRT) models for unfolding processes use the responses of individuals to attitudinal tests or questionnaires in order to infer item and person parameters located on a latent continuum. Parametric models in this class use parametric functions to model the response process, which in practice can be restrictive. MUDFOLD (Multiple UniDimensional unFOLDing) can be used to obtain estimates of person and item ranks without imposing strict parametric assumptions on the item response functions (IRFs). This paper describes the implementation of the MUDFOLD method for binary preferential-choice data in the R package mudfold. The latter incorporates estimation, visualization, and simulation methods in order to provide R users with utilities for nonparametric analysis of attitudinal questionnaire data. After a brief introduction in IRT, we provide the method ological framework implemented in the package. A description of the available functions is followed by practical examples and suggestions on how this method can be used even outside the field of psychometrics.

Received: 2018-12-11; online 2020-03-31, supplementary material, (2.4 Kb)
CRAN packages: mudfold, GGUM, mirt, mokken, boot, mice, gtools, glmnet, mgcv, zoo, reshape2, ggplot2, smacof
CRAN Task Views cited directly: Psychometrics
CRAN Task Views implied by cited CRAN packages: Psychometrics, Econometrics, MissingData, SocialSciences, Environmetrics, Survival, TimeSeries, Bayesian, Finance, Graphics, MachineLearning, Multivariate, OfficialStatistics, Optimization, Phylogenetics, TeachingStatistics


CC BY 4.0
This article and supplementary materials are licensed under a Creative Commons Attribution 4.0 International license.

@article{RJ-2020-002,
  author = {Spyros E. Balafas and Wim P. Krijnen and Wendy J. Post and
          Ernst C. Wit},
  title = {{mudfold: An R Package for Nonparametric IRT Modelling of
          Unfolding Processes}},
  year = {2020},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2020-002},
  url = {https://journal.r-project.org/archive/2020/RJ-2020-002/index.html}
}