Effect of item redundancy on Rasch item and person estimates.

One of the assumptions of many latent trait models is local independence. This assumption specifies that, after controlling for the underlying trait, item responses are independent. Given the lack of studies of model robustness against such violations, it appears that this assumption is frequently taken for granted. Therefore, this study investigated the robustness of Rasch item and person estimates with simulated data under varying number of items, sample sizes, and levels of item redundancy. Item and person reliabilities, the standard deviations of the person and item estimates, the root mean squared differences and mean signed differences among person and item estimates, the correlations between person estimates, and the percentage of person estimates shifting by more than .50 logits were used to evaluate the impact of item redundancy. Both norm and criterion-reference interpretations may be influenced by the imputation of redundancy into the data. However, it appears that the amount of redundancy needs to be considerable before such interpretations would be adversely impacted. Suggestions for further simulation research are provided.