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Exact group sequential designs for two-arm experiments with Poisson distributed outcome variables
We describe and compare two methods for the group sequential design of two-arm experiments with Poisson distributed data, which are based on a normal approximation and exact calculations respectively. A framework to determine near-optimal stopping boundaries is also presented. Using this framework,...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7116540/ https://www.ncbi.nlm.nih.gov/pubmed/33408437 http://dx.doi.org/10.1080/03610926.2019.1628273 |
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author | Grayling, Michael J. Wason, James M. S. Mander, Adrian P. |
author_facet | Grayling, Michael J. Wason, James M. S. Mander, Adrian P. |
author_sort | Grayling, Michael J. |
collection | PubMed |
description | We describe and compare two methods for the group sequential design of two-arm experiments with Poisson distributed data, which are based on a normal approximation and exact calculations respectively. A framework to determine near-optimal stopping boundaries is also presented. Using this framework, for a considered example, we demonstrate that a group sequential design could reduce the expected sample size under the null hypothesis by as much as 44% compared to a fixed sample approach. We conclude with a discussion of the advantages and disadvantages of the two presented procedures. |
format | Online Article Text |
id | pubmed-7116540 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
record_format | MEDLINE/PubMed |
spelling | pubmed-71165402021-01-05 Exact group sequential designs for two-arm experiments with Poisson distributed outcome variables Grayling, Michael J. Wason, James M. S. Mander, Adrian P. Commun Stat Theory Methods Article We describe and compare two methods for the group sequential design of two-arm experiments with Poisson distributed data, which are based on a normal approximation and exact calculations respectively. A framework to determine near-optimal stopping boundaries is also presented. Using this framework, for a considered example, we demonstrate that a group sequential design could reduce the expected sample size under the null hypothesis by as much as 44% compared to a fixed sample approach. We conclude with a discussion of the advantages and disadvantages of the two presented procedures. 2021 2019-06-17 /pmc/articles/PMC7116540/ /pubmed/33408437 http://dx.doi.org/10.1080/03610926.2019.1628273 Text en Published with license by Taylor & Francis Group, LLC 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 use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Article Grayling, Michael J. Wason, James M. S. Mander, Adrian P. Exact group sequential designs for two-arm experiments with Poisson distributed outcome variables |
title | Exact group sequential designs for two-arm experiments with Poisson distributed outcome variables |
title_full | Exact group sequential designs for two-arm experiments with Poisson distributed outcome variables |
title_fullStr | Exact group sequential designs for two-arm experiments with Poisson distributed outcome variables |
title_full_unstemmed | Exact group sequential designs for two-arm experiments with Poisson distributed outcome variables |
title_short | Exact group sequential designs for two-arm experiments with Poisson distributed outcome variables |
title_sort | exact group sequential designs for two-arm experiments with poisson distributed outcome variables |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7116540/ https://www.ncbi.nlm.nih.gov/pubmed/33408437 http://dx.doi.org/10.1080/03610926.2019.1628273 |
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