extended · other · 2025

Detecting item misfit in Rasch models

Magnus Johansson; Richard M. Smith

Psychometrics in general have long relied on rule-of-thumb critical values forvarious goodness of fit metrics. With more powerful personal computers it is bothfeasible and desirable to use simulation and/or bootstrap methods to determineappropriate cutoff values. This paper illustrates and evaluates the use of an R pack-age for Rasch psychometrics that has implemented functions to simplify the pro-cess of determining simulation-based cutoff values. Through a series of simulationstudies, a comparison is made between the two methods of information-weightedconditional item fit (“infit”) and item-restscore correlations using Goodman andKruskal’s 𝛾. Results indicate the limitations of small samples (n < 500) in cor-rectly detecting item misfit due to multidimensionality, especially when a largerproportion of items are misfit and misfit items are off-target. Item outfit showsvery low p...