ArticleBMC medical research methodology2008
Rasch fit statistics and sample size considerations for polytomous data.
Article in BMC medical research methodology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 137 papers.
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Who cites it
137 citing papers in PubMed.
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- Web-based and mixed-mode cognitive large-scale assessments in higher education: An evaluation of selection bias, measurement bias, and prediction bias.Behavior research methods · 2021Trial
- Validation of the food access survey tool to assess household food insecurity in rural Bangladesh.BMC public health · 2015Trial
- Trial
- Understanding Holistic Patient-Relevant Measurement in Amyotrophic Lateral Sclerosis: A Mixed-Methods Content Validity and Exploratory Rasch Analysis of Selected Clinical Outcome Assessments.Neurology and therapy · 2026Article
- Cultural Adaptation and Psychometric Validation of a Thai Version of the Turnover Intention Scale (T-TIS) for Thai Nursing Professionals.Nursing open · 2026Article
- Transforaminal Endoscopic Lumbar Decompression: Defining Its Scope and Limitations.International journal of spine surgery · 2026Article
- Observational
- The adult social care outcomes toolkit easy read for older people (ASCOT-ER OP): an exploratory factor analysis and Rasch validation study.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2026Article
- Evaluating and refining the wheelchair mobility activity log (WC-MAL): a comprehensive study of validity and reliability.Spinal cord · 2026Article
- Mapping Competence in Gastrointestinal Endoscopy Nursing Practice: An Item Response Theory Analysis of Perceived Skill Acquisition and Maintenance in Italy.Healthcare (Basel, Switzerland) · 2026Article
- Cross-cultural adaptation of evidence-based practice measure among Hong Kong healthcare providers.PloS one · 2026Article
- Measuring navigational and digital health literacy in individuals with long-term conditions: latent trait analyses using Rasch modelling.Frontiers in public health · 2026Article
- Cross-Cultural Adaptation and Psychometric Evaluation of the Persian Version of the ADL Taxonomy Questionnaire in Persons With Stroke: A Rasch Analysis.Occupational therapy international · 2026Article
- Development and Rasch Validation of the Parental Topical Corticosteroid Phobia Scale (PTCPS) in Pediatric Eczema Care.Healthcare (Basel, Switzerland) · 2025Article
- Assessing Language Skills in Children Aged 4 to 6 Years with Autism Spectrum Disorder: A Prospective Study.Children (Basel, Switzerland) · 2025Article
- The Reduced Multi-Dimensional Health Literacy Scale: A First Bilingual Validation Using RASCH Analysis.International journal of environmental research and public health · 2025Article
- Validity of the Connor Davidson Resilience Scale (CD-RISC) in adolescents and young adults in Sweden: a think aloud approach combined with a Rasch analysis.Health and quality of life outcomes · 2025Article
- Validation of the Psychometric Properties of the German Version of OBI-Care in Informal Caregivers of Stroke Survivors.Journal of clinical medicine · 2025Article
- Development of a cannabis health literacy questionnaire: preliminary validation using the Rasch model.BMC public health · 2025Article
77 more citing papers are in PubMed but not listed here.
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Abstract
backgroundPrevious research on educational data has demonstrated that Rasch fit statistics (mean squares and t-statistics) are highly susceptible to sample size variation for dichotomously scored rating data, although little is known about this relationship for polytomous data. These statistics help inform researchers about how well items fit to a unidimensional latent trait, and are an important adjunct to modern psychometrics. Given the increasing use of Rasch models in health research the purpose of this study was therefore to explore the relationship between fit statistics and sample size for polytomous data.
methodsData were collated from a heterogeneous sample of cancer patients (n = 4072) who had completed both the Patient Health Questionnaire - 9 and the Hospital Anxiety and Depression Scale. Ten samples were drawn with replacement for each of eight sample sizes (n = 25 to n = 3200). The Rating and Partial Credit Models were applied and the mean square and t-fit statistics (infit/outfit) derived for each model.
resultsThe results demonstrated that t-statistics were highly sensitive to sample size, whereas mean square statistics remained relatively stable for polytomous data.
conclusionIt was concluded that mean square statistics were relatively independent of sample size for polytomous data and that misfit to the model could be identified using published recommended ranges.
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