Non-ignorable missingness item response theory models for choice effects in examinee-selected items

Chen Wei Liu*, Wen Chung Wang

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

5 引文 斯高帕斯(Scopus)

摘要

Examinee-selected item (ESI) design, in which examinees are required to respond to a fixed number of items in a given set, always yields incomplete data (i.e., when only the selected items are answered, data are missing for the others) that are likely non-ignorable in likelihood inference. Standard item response theory (IRT) models become infeasible when ESI data are missing not at random (MNAR). To solve this problem, the authors propose a two-dimensional IRT model that posits one unidimensional IRT model for observed data and another for nominal selection patterns. The two latent variables are assumed to follow a bivariate normal distribution. In this study, the mirt freeware package was adopted to estimate parameters. The authors conduct an experiment to demonstrate that ESI data are often non-ignorable and to determine how to apply the new model to the data collected. Two follow-up simulation studies are conducted to assess the parameter recovery of the new model and the consequences for parameter estimation of ignoring MNAR data. The results of the two simulation studies indicate good parameter recovery of the new model and poor parameter recovery when non-ignorable missing data were mistakenly treated as ignorable.

原文英語
頁(從 - 到)499-524
頁數26
期刊British Journal of Mathematical and Statistical Psychology
70
發行號3
DOIs
出版狀態已發佈 - 2017 十一月
對外發佈

ASJC Scopus subject areas

  • 統計與概率
  • 藝術與人文(雜項)
  • 心理學(全部)

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