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Why are two mistakes not worse than one? A proposal for controlling the expected number of false claims

Multiplicity is common in clinical studies and the current standard is to use the familywise error rate to ensure that the errors are kept at a prespecified level. In this paper, we will show that, in certain situations, familywise error rate control does not account for all errors made. To countera...

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Detalles Bibliográficos
Autores principales: Jaki, Thomas, Parry, Alice
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5021178/
https://www.ncbi.nlm.nih.gov/pubmed/27094960
http://dx.doi.org/10.1002/pst.1751
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author Jaki, Thomas
Parry, Alice
author_facet Jaki, Thomas
Parry, Alice
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description Multiplicity is common in clinical studies and the current standard is to use the familywise error rate to ensure that the errors are kept at a prespecified level. In this paper, we will show that, in certain situations, familywise error rate control does not account for all errors made. To counteract this problem, we propose the use of the expected number of false claims (EFC). We will show that a (weighted) Bonferroni approach can be used to control the EFC, discuss how a study that uses the EFC can be powered for co‐primary, exchangeable, and hierarchical endpoints, and show how the weight for the weighted Bonferroni test can be determined in this manner. ©2016 The Authors. Pharmaceutical Statistics Published by John Wiley & Sons Ltd.
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spelling pubmed-50211782016-09-23 Why are two mistakes not worse than one? A proposal for controlling the expected number of false claims Jaki, Thomas Parry, Alice Pharm Stat Main Papers Multiplicity is common in clinical studies and the current standard is to use the familywise error rate to ensure that the errors are kept at a prespecified level. In this paper, we will show that, in certain situations, familywise error rate control does not account for all errors made. To counteract this problem, we propose the use of the expected number of false claims (EFC). We will show that a (weighted) Bonferroni approach can be used to control the EFC, discuss how a study that uses the EFC can be powered for co‐primary, exchangeable, and hierarchical endpoints, and show how the weight for the weighted Bonferroni test can be determined in this manner. ©2016 The Authors. Pharmaceutical Statistics Published by John Wiley & Sons Ltd. John Wiley and Sons Inc. 2016-04-20 2016 /pmc/articles/PMC5021178/ /pubmed/27094960 http://dx.doi.org/10.1002/pst.1751 Text en ©2016 The Authors. Pharmaceutical Statistics Published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs (http://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Main Papers
Jaki, Thomas
Parry, Alice
Why are two mistakes not worse than one? A proposal for controlling the expected number of false claims
title Why are two mistakes not worse than one? A proposal for controlling the expected number of false claims
title_full Why are two mistakes not worse than one? A proposal for controlling the expected number of false claims
title_fullStr Why are two mistakes not worse than one? A proposal for controlling the expected number of false claims
title_full_unstemmed Why are two mistakes not worse than one? A proposal for controlling the expected number of false claims
title_short Why are two mistakes not worse than one? A proposal for controlling the expected number of false claims
title_sort why are two mistakes not worse than one? a proposal for controlling the expected number of false claims
topic Main Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5021178/
https://www.ncbi.nlm.nih.gov/pubmed/27094960
http://dx.doi.org/10.1002/pst.1751
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