Abstract
BackgroundComputerized adaptive testing (CAT) utilizes latent variable measurement model parameters that are typically assumed to be equivalently applicable to all people. Biased latent variable scores may be obtained in samples that are heterogeneous with respect to a specified measurement model. We examined the implications of sample heterogeneity with respect to CAT-predicted patient-reported outcomes (PRO) scores for the measurement of pain.MethodsA latent variable mixture modeling (LVMM) analysis was conducted using data collected from a heterogeneous sample of people in British Columbia, Canada, who were administered the 36 pain domain items of the CAT-5D-QOL. The fitted LVMM was then used to produce data for a simulation analysis. We evaluated bias by comparing the referent PRO scores of the LVMM with PRO scores predicted by a “conventional” CAT (ignoring heterogeneity) and a LVMM-based “mixture” CAT (accommodating heterogeneity).ResultsThe LVMM analysis indicated support for three latent classes with class proportions of 0.25, 0.30 and 0.45, which suggests that the sample was heterogeneous. The simulation analyses revealed differences between the referent PRO scores and the PRO scores produced by the “conventional” CAT. The “mixture” CAT produced PRO scores that were nearly equivalent to the referent scores.ConclusionBias in PRO scores based on latent variable models may result when population heterogeneity is ignored. Improved accuracy could be obtained by using CATs that are parameterized using LVMM.
Highlights
Computerized adaptive tests (CATs) increasingly are used to quantify health-related concepts, including patient reported outcomes (PROs) pertaining to symptoms, functional status, and mental health [1,2,3,4,5,6,7,8]
The latent variable mixture modeling (LVMM) analysis indicated support for three latent classes with class proportions of 0.25, 0.30 and 0.45, which suggests that the sample was heterogeneous
The simulation analyses revealed differences between the referent PRO scores and the PRO scores produced by the “conventional” CAT
Summary
Computerized adaptive testing (CAT) utilizes latent variable measurement model parameters that are typically assumed to be equivalently applicable to all people. Biased latent variable scores may be obtained in samples that are heterogeneous with respect to a specified measurement model. We examined the implications of sample heterogeneity with respect to CAT-predicted patient-reported outcomes (PRO) scores for the measurement of pain. Data Availability Statement: All files are available from the figshare database: 1) Data file: figshare.com/ s/a037096ce7bc11e4af3506ec4b8d1f61 2) Documentation: figshare.com/s/ b76ac7e0e7bc11e4a69506ec4b8d1f61. Funding for data collection and preliminary analyses was received from the Canadian Arthritis Network and Arthritis Research Canada. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
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