A NEW MODEL FOR CATEGORY-SCALING DATA WITH AN APPLICATION TO THE DEVELOPMENT OF HEALTH-STATUS MEASURES

Category rating is used to assess patient, family-member, provider, an d societal preferences for health outcomes. Often, it is of interest t o compare ratings obtained from different groups. Standard methods for making comparisons, such as regressions, correlations, and multiple t -tests, do not account for the dependency among ratings. The authors p ropose a new model for category ratings that does consider their relat ive dependency. This model provides a profile of ratings for a single group and facilitates comparisons across groups. It was applied to cat egory ratings for four levels of Bending and Lifting function as defin ed by the recently developed Functional Capacity Index (FCI). Differen ces in ratings were observed across groups with different personal exp eriences of functional limitations and across groups with different de grees oi clinical knowledge. These differences were not observed when standard methods were used. Thus, ignoring the relative nature of cate gory ratings can lead to different conclusions about group preferences for health outcomes. When the ratings are being used to scale a healt h-status measure, this discrepancy has implications for the applicatio n of the measure in resource allocation.