A Novel Method for Expediting the Development of Patient-Reported Outcome Measures and an Evaluation Across Several Populations

dc.contributor.authorGarrard, Lili
dc.contributor.authorPrice, Larry R.
dc.contributor.authorBott, Marjorie J.
dc.contributor.authorGajewski, Byron J.
dc.date.accessioned2019-07-29T16:18:03Z
dc.date.available2019-07-29T16:18:03Z
dc.date.issued2016-01
dc.description.abstractItem response theory (IRT) models provide an appropriate alternative to the classical ordinal confirmatory factor analysis (CFA) during the development of patient-reported outcome measures (PROMs). Current literature has identified the assessment of IRT model fit as both challenging and underdeveloped. This study evaluates the performance of Ordinal Bayesian Instrument Development (OBID), a Bayesian IRT model with a probit link function approach, through applications in two breast cancer-related instrument development studies. The primary focus is to investigate an appropriate method for comparing Bayesian IRT models in PROMs development. An exact Bayesian leave-one-out cross-validation (LOO-CV) approach is implemented to assess prior selection for the item discrimination parameter in the IRT model and subject content experts’ bias (in a statistical sense and not to be confused with psychometric bias as in differential item functioning) toward the estimation of item-to-domain correlations. Results support the utilization of content subject experts’ information in establishing evidence for construct validity when sample size is small. However, the incorporation of subject experts’ content information in the OBID approach can be sensitive to the level of expertise of the recruited experts. More stringent efforts need to be invested in the appropriate selection of subject experts to efficiently use the OBID approach and reduce potential bias during PROMs development.
dc.description.departmentCounseling, Leadership, Adult Education, and School Psychology
dc.description.versionThis is the accepted manuscript version of an article published in Applied Psychological Measurement.
dc.formatText
dc.format.extent9 pages
dc.format.medium1 file (.pdf)
dc.identifier.citationGarrard, L., Price, L. R., Bott, M. J., & Gajewski, B. J. (2016). A Novel Method for Expediting the Development of Patient-Reported Outcome Measures and an Evaluation Across Several Populations. Applied Psychological Measurement, 40(7), pp. 455–468.
dc.identifier.doihttps://doi.org/10.1177/0146621616652634
dc.identifier.urihttps://hdl.handle.net/10877/8407
dc.language.isoen
dc.publisherSage
dc.sourceApplied Psychological Measurement, 2016, Vol. 40, No. 7, pp. 455–468.
dc.subjectBayesian leave-one-out cross-validation
dc.subjectBayesian IRT
dc.subjectBayesian model comparison
dc.subjectpatient-reported outcome measures
dc.subjectPROMs
dc.subjectOBID
dc.subjectCounseling, Leadership, Adult Education, and School Psychology
dc.titleA Novel Method for Expediting the Development of Patient-Reported Outcome Measures and an Evaluation Across Several Populations
dc.typeArticle

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