ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2024
Power analyses for measurement model misspecification and response shift detection with structural equation modeling.
Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Response shift results of quantitative research using patient-reported outcome measures: a meta-regression analysis.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025Pooled it
- Praxis function in the ADL Observation Scale: Spanish cross-cultural adaptation and psychometric properties.PloS one · 2026Article
- Leading with Integrity: Impact of Ethical Leadership on Performance of Healthcare Professionals in Saudi Arabia.Healthcare (Basel, Switzerland) · 2025Article
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Abstract
purposeStatistical power for response shift detection with structural equation modeling (SEM) is currently underreported. The present paper addresses this issue by providing worked-out examples and syntaxes of power calculations relevant for the statistical tests associated with the SEM approach for response shift detection.
methodsPower calculations and related sample-size requirements are illustrated for two modelling goals: (1) to detect misspecification in the measurement model, and (2) to detect response shift. Power analyses for hypotheses regarding (exact) overall model fit and the presence of response shift are demonstrated in a step-by-step manner. The freely available and user-friendly R-package lavaan and shiny-app 'power4SEM' are used for the calculations.
resultsUsing the SF-36 as an example, we illustrate the specification of null-hypothesis (H
conclusionBy providing accessible resources to perform power analyses and emphasizing the different power analyses associated with different modeling goals, we hope to facilitate the uptake of power analyses for response shift detection with SEM and thereby enhance the stringency of response shift research.
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