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Tytuł:
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Present state bias in transition ratings was accurately estimated in simulated and real data.
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Autorzy:
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Terluin B; Department of General Practice, Amsterdam Public Health research institute, Amsterdam UMC, Vrije Universiteit Amsterdam, de Boelelaan 1117, 1081 HV Amsterdam, The Netherlands. Electronic address: .
Griffiths P; Patient Centered Endpoints, IQVIA, Reading, United Kingdom. Electronic address: .
Trigg A; Patient-Centered Outcomes, Adelphi Values, Adelphi Mill, Bollington, Cheshire, SK10 5JB, United Kingdom. Electronic address: .
Terwee CB; Department of Epidemiology and Data Science, Amsterdam Public Health research institute, Amsterdam UMC, Vrije Universiteit Amsterdam, de Boelelaan 1117, 1081 HV Amsterdam, The Netherlands. Electronic address: .
Bjorner JB; QualityMetric, Johnston, RI, USA; Department of Public Health, University of Copenhagen, Copenhagen, Denmark. Electronic address: .
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Źródło:
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Journal of clinical epidemiology [J Clin Epidemiol] 2022 Mar; Vol. 143, pp. 128-136. Date of Electronic Publication: 2021 Dec 26.
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Typ publikacji:
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Journal Article
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Język:
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English
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Imprint Name(s):
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Publication: New York : Elsevier
Original Publication: Oxford ; New York : Pergamon Press, c1988-
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MeSH Terms:
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Reproducibility of Results*
Bias ; Factor Analysis, Statistical ; Humans ; Surveys and Questionnaires
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Contributed Indexing:
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Keywords: Minimal important change; Patient-reported outcomes; Present state bias; Reliability; Transition ratings; Validity
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Entry Date(s):
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Date Created: 20211229 Date Completed: 20220503 Latest Revision: 20220609
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Update Code:
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20240104
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DOI:
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10.1016/j.jclinepi.2021.12.024
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PMID:
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34965478
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Objective: Patient-reported transition ratings are supposed to reflect the change between a previous baseline health state and a present follow-up state, but may reflect the present state to a greater extent. This so-called "present state bias" (PSB) potentially threatens the validity of transition ratings. Several criteria have been proposed to assess PSB. We examined how well these criteria perform and to which extent confirmatory factor analysis (CFA) for categorical data provides an accurate assessment of the degree of PSB.
Study Design and Setting: We simulated multiple samples with baseline and follow-up item responses to a hypothetical questionnaire, and transition ratings. The samples varied with respect to various distributional characteristics and the degree of PSB. The performance of criteria proposed in the literature, and a new CFA-based criterion, were evaluated by the proportion of explained variance in PSB. In addition, four real datasets were analyzed.
Results: The known criteria explained 36-74% of the variance in PSB. A new CFA-based criterion, namely the ratio of the factor loadings of the transition ratings plus one, explained 81-98% of the variance in PSB across the samples.
Conclusion: Present state bias in transition ratings can be estimated accurately using CFA.
(Copyright © 2021. Published by Elsevier Inc.)
