Estimating person locations from partial credit data containing missing responses.

Abstract

Certain assessment situations produce partial credit data. For instance, performance assessment items may utilize a rubric that assigns partial credit for some not completely correct responses. In some cases examinees may choose to not answer each question. This study investigated the effect of various strategies for handling these missing responses for estimating a respondent's location. These methods included ignoring the omitted response, selecting the "midpoint" category score, treating the omitted response as incorrect, hotdecking, and a likelihood-based approach. A simulation study was performed to examine the efficacy of these methods with the partial credit and generalized partial credit models. Expected a posteriori (EAP) ability estimation was used. Results showed that the Midpoint and Likelihood procedures performed the best of methods examined. In contrast, omitted responses should not be treated as incorrect nor ignored when estimating an examinee's proficiency using EAP. Implications for practitioners are discussed.