Parameter recovery for the partial credit model using MULTILOG.

Abstract

This study investigated parameter recovery for the partial credit model using the MULTILOG computer program. Factors studied were the sample size and the number of item parameters, which were manipulated by systematically varying the number of steps per item and the number of items. The findings suggest that the ratio of sample size to number of item parameters being estimated as a "rule of thumb" can be a more complete guideline when the number of steps per item is taken into account. Accurate estimation of ability can be obtained across all conditions, even with sample sizes as small as 250. With regard to estimation of step values, however, more caution is warranted. Accurate estimation of the step values of items which have more categories requires larger sample sizes for a given number of total parameters to be estimated.