Fitting item response unfolding models to Likert-scale data using mirt in R

Chen Wei Liu, R. Philip Chalmers*

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

10 引文 斯高帕斯(Scopus)

摘要

While a large family of unfolding models for Likert-scale response data have been developed for decades, very few applications of these models have been witnessed in practice. There may be several reasons why these have not appeared more widely in published research, however one obvious limitation appears to be the absence of suitable software for model estimation. In this article, the authors demonstrate how the mirt package can be adopted to estimate parameters from various unidimensional and multidimensional unfolding models. To concretely demonstrate the concepts and recommendations, a tutorial and examples of R syntax are provided for practical guidelines. Finally, the performance of mirt is evaluated via parameter-recovery simulation studies to demonstrate its potential effectiveness. The authors argue that, armed with the mirt package, applying unfolding models to Likert-scale data is now not only possible but can be estimated to real-datasets with little difficulty.

原文英語
文章編號e0196292
期刊PloS one
13
發行號5
DOIs
出版狀態已發佈 - 2018 5月
對外發佈

ASJC Scopus subject areas

  • 多學科

指紋

深入研究「Fitting item response unfolding models to Likert-scale data using mirt in R」主題。共同形成了獨特的指紋。

引用此