Modified Item-Fit Indices for Dichotomous IRT Models with Missing Data.

ABSTRACT: Item-level fit analysis not only serves as a complementary check to global fit analysis, it is also essential in scale development because the fit results will guide item revision and/or deletion (Liu & Maydeu-Olivares, 2014). During data collection, missing response data may likely happen due to various reasons. Chi-square-based item fit indices (e.g., Yen's Q ₁ , McKinley and Mill's G ² , Orlando and Thissen's S-X ² and S-G ² ) are the most widely used statistics to assess item-level fit. However, the role of total scores with complete data used in S-X ² and S-G ² is different from that with incomplete data. As a result, S-X

SUBMITTER: Zhang X 

PROVIDER: S-EPMC9574083 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature