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Power calculator for instrumental variable analysis in pharmacoepidemiology

BACKGROUND: Instrumental variable analysis, for example with physicians’ prescribing preferences as an instrument for medications issued in primary care, is an increasingly popular method in the field of pharmacoepidemiology. Existing power calculators for studies using instrumental variable analysi...

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Detalles Bibliográficos
Autores principales: Walker, Venexia M, Davies, Neil M, Windmeijer, Frank, Burgess, Stephen, Martin, Richard M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5837396/
https://www.ncbi.nlm.nih.gov/pubmed/28575313
http://dx.doi.org/10.1093/ije/dyx090
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author Walker, Venexia M
Davies, Neil M
Windmeijer, Frank
Burgess, Stephen
Martin, Richard M
author_facet Walker, Venexia M
Davies, Neil M
Windmeijer, Frank
Burgess, Stephen
Martin, Richard M
author_sort Walker, Venexia M
collection PubMed
description BACKGROUND: Instrumental variable analysis, for example with physicians’ prescribing preferences as an instrument for medications issued in primary care, is an increasingly popular method in the field of pharmacoepidemiology. Existing power calculators for studies using instrumental variable analysis, such as Mendelian randomization power calculators, do not allow for the structure of research questions in this field. This is because the analysis in pharmacoepidemiology will typically have stronger instruments and detect larger causal effects than in other fields. Consequently, there is a need for dedicated power calculators for pharmacoepidemiological research. METHODS AND RESULTS: The formula for calculating the power of a study using instrumental variable analysis in the context of pharmacoepidemiology is derived before being validated by a simulation study. The formula is applicable for studies using a single binary instrument to analyse the causal effect of a binary exposure on a continuous outcome. An online calculator, as well as packages in both R and Stata, are provided for the implementation of the formula by others. CONCLUSIONS: The statistical power of instrumental variable analysis in pharmacoepidemiological studies to detect a clinically meaningful treatment effect is an important consideration. Research questions in this field have distinct structures that must be accounted for when calculating power. The formula presented differs from existing instrumental variable power formulae due to its parametrization, which is designed specifically for ease of use by pharmacoepidemiologists.
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spelling pubmed-58373962018-03-09 Power calculator for instrumental variable analysis in pharmacoepidemiology Walker, Venexia M Davies, Neil M Windmeijer, Frank Burgess, Stephen Martin, Richard M Int J Epidemiol Methods BACKGROUND: Instrumental variable analysis, for example with physicians’ prescribing preferences as an instrument for medications issued in primary care, is an increasingly popular method in the field of pharmacoepidemiology. Existing power calculators for studies using instrumental variable analysis, such as Mendelian randomization power calculators, do not allow for the structure of research questions in this field. This is because the analysis in pharmacoepidemiology will typically have stronger instruments and detect larger causal effects than in other fields. Consequently, there is a need for dedicated power calculators for pharmacoepidemiological research. METHODS AND RESULTS: The formula for calculating the power of a study using instrumental variable analysis in the context of pharmacoepidemiology is derived before being validated by a simulation study. The formula is applicable for studies using a single binary instrument to analyse the causal effect of a binary exposure on a continuous outcome. An online calculator, as well as packages in both R and Stata, are provided for the implementation of the formula by others. CONCLUSIONS: The statistical power of instrumental variable analysis in pharmacoepidemiological studies to detect a clinically meaningful treatment effect is an important consideration. Research questions in this field have distinct structures that must be accounted for when calculating power. The formula presented differs from existing instrumental variable power formulae due to its parametrization, which is designed specifically for ease of use by pharmacoepidemiologists. Oxford University Press 2017-10 2017-05-30 /pmc/articles/PMC5837396/ /pubmed/28575313 http://dx.doi.org/10.1093/ije/dyx090 Text en © The Author 2017. Published by Oxford University Press on behalf of the International Epidemiological Association http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methods
Walker, Venexia M
Davies, Neil M
Windmeijer, Frank
Burgess, Stephen
Martin, Richard M
Power calculator for instrumental variable analysis in pharmacoepidemiology
title Power calculator for instrumental variable analysis in pharmacoepidemiology
title_full Power calculator for instrumental variable analysis in pharmacoepidemiology
title_fullStr Power calculator for instrumental variable analysis in pharmacoepidemiology
title_full_unstemmed Power calculator for instrumental variable analysis in pharmacoepidemiology
title_short Power calculator for instrumental variable analysis in pharmacoepidemiology
title_sort power calculator for instrumental variable analysis in pharmacoepidemiology
topic Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5837396/
https://www.ncbi.nlm.nih.gov/pubmed/28575313
http://dx.doi.org/10.1093/ije/dyx090
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