UCLA

As part of a scale development project, we fit a nominal response item response theory model to responses to the Health Care Engagement Measure (HEM). When using the original 5-point response format, categories were not ordered as intended for six of the 23 items. For the remaining, the category boundary discrimination between Categories 0 (not at all true) and 1 (a little bit true) was only weakly discriminating, suggesting uninformative categories. When the lowest two categories were collapsed, psychometric properties improved greatly. Category boundary discriminations within items, however, varied significantly. Specifically, higher response category distinctions, such as responding 3 (very true) versus 2 (mostly true) were considerably more discriminating than lower response category distinctions. Implications for HEM scoring and for improving measurement precision at lower levels of the construct are presented as is the unique role of the nominal response model in category analysis.