Department of Quantitative Health Sciences
Health Services Administration | Psychiatric and Mental Health | Psychiatry and Psychology
BACKGROUND: Recently, a growing number of Item-Response Theory (IRT) models has been published, which allow estimation of a common latent variable from data derived by different Patient Reported Outcomes (PROs). When using data from different PROs, direct estimation of the latent variable has some advantages over the use of sum score conversion tables. It requires substantial proficiency in the field of psychometrics to fit such models using contemporary IRT software. We developed a web application ( http://www.common-metrics.org ), which allows estimation of latent variable scores more easily using IRT models calibrating different measures on instrument independent scales.
RESULTS: Currently, the application allows estimation using six different IRT models for Depression, Anxiety, and Physical Function. Based on published item parameters, users of the application can directly estimate latent trait estimates using expected a posteriori (EAP) for sum scores as well as for specific response patterns, Bayes modal (MAP), Weighted likelihood estimation (WLE) and Maximum likelihood (ML) methods and under three different prior distributions. The obtained estimates can be downloaded and analyzed using standard statistical software.
CONCLUSIONS: This application enhances the usability of IRT modeling for researchers by allowing comparison of the latent trait estimates over different PROs, such as the Patient Health Questionnaire Depression (PHQ-9) and Anxiety (GAD-7) scales, the Center of Epidemiologic Studies Depression Scale (CES-D), the Beck Depression Inventory (BDI), PROMIS Anxiety and Depression Short Forms and others. Advantages of this approach include comparability of data derived with different measures and tolerance against missing values. The validity of the underlying models needs to be investigated in the future.
Anxiety, Depression, Item-Response Theory, Measurement, Patient Reported Outcomes, Physical function
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Copyright © The Author(s). 2016
DOI of Published Version
BMC Med Res Methodol. 2016 Oct 19;16(1):142. Link to article on publisher's site
BMC medical research methodology
Fischer, H. Felix and Rose, Matthias S. F., "www.common-metrics.org: a web application to estimate scores from different patient-reported outcome measures on a common scale" (2016). Open Access Articles. 2958.
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This work is licensed under a Creative Commons Attribution 4.0 License.