Practical Issues in the Application of Item Response Theory

Abstract

Item response theory (IRT) is increasingly being applied to health-related quality of life instrument development and refinement. This article discusses results obtained using categorical confirmatory factor analysis (CCFA) to check IRT model assumptions and the application of IRT in item analysis and scale evaluation. To demonstrate the value of CCFA and IRT in examining a health-related quality of life measure in children and adolescents. This illustration uses data from 10,241 children and their parents on items from the 4 subscales of the PedsQL 4.0 Generic Core Scales. CCFA was applied to confirm domain dimensionality and identify possible locally dependent items. IRT was used to assess the strength of the relationship between the items and the constructs of interest and the information available across the latent construct. CCFA showed generally strong support for 1-factor models for each domain; however, several items exhibited evidence of local dependence. IRT revealed that the items generally exhibit favorable characteristics and are related to the same construct within a given domain. We discuss the lessons that can be learned by comparing alternate forms of the same scale, and we assess the potential impact of local dependence on the item parameter estimates. This article describes CCFA methods for checking IRT model assumptions and provides suggestions for using these methods in practice. It offers insight into ways information gained through IRT can be applied to evaluate items and aid in scale construction.