A bootstrap approach to evaluating person and item fit to the Rasch model

Abstract

Historically, rule-of-thumb critical values have been employed for interpreting fit statistics that depict anomalous person and item response patterns in applications of the Rasch model. Unfortunately, prior research has shown that these values are not appropriate in many contexts. This article introduces a bootstrap procedure for identifying reasonable critical values for Rasch fit statistics and compares the results of that procedure to applications of rule-of-thumb critical values for three example datasets. The results indicate that rule-of-thumb values may over- or under-identify the number of misfitting items or persons.