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Simplification or simulation: Power calculation in clinical trials.
Huang, Chao; Li, Pute; Martin, Colin R.
Afiliación
  • Huang C; Hull York Medical School, University of Hull, UK. Electronic address: chao.huang@hyms.ac.uk.
  • Li P; School of Professional Study, New York University, USA.
  • Martin CR; Institute for Health and Wellbeing, University of Suffolk, UK.
Contemp Clin Trials ; 113: 106663, 2022 02.
Article en En | MEDLINE | ID: mdl-34958933
BACKGROUND AND OBJECTIVES: A justifiable sample size is essential at trial design stage. Generally this task is completed by forming the main research question into a statistical procedure and then implementing the published formulae or software packages. When these standard statistical formulae/software packages become unavailable for studies with complex statistical procedures, some statisticians choose to fill this gap by assuming an alternative simplified sample size calculation. Monte Carlo simulations can also be deployed, particularly for complex trials. However, it is still unclear on how to determine the appropriate approach under certain practical scenarios. METHODS: We adopted real clinical trials as examples and investigated on simplification and simulation-based sample size calculation approaches. RESULTS: Compared to simplified sample size calculation, the simulation approach can better address the non-ignorable impact of baseline/follow-up outcome correlation on study power. For studies with multiple endpoints and multiple co-primary endpoints, the sample sizes calculated by simplification approach should be scrutinized. CONCLUSIONS: Directly using the simplification approach for sample size calculation should be restricted. We recommend to utilize the simulation approach, particularly for complex trials, at least as a sensitivity checking and a useful triangulation to the simplification approach outlined.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Proyectos de Investigación / Modelos Estadísticos Tipo de estudio: Health_economic_evaluation / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Contemp Clin Trials Asunto de la revista: MEDICINA / TERAPEUTICA Año: 2022 Tipo del documento: Article Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Proyectos de Investigación / Modelos Estadísticos Tipo de estudio: Health_economic_evaluation / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Contemp Clin Trials Asunto de la revista: MEDICINA / TERAPEUTICA Año: 2022 Tipo del documento: Article Pais de publicación: Estados Unidos