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Power calculations for cluster randomized trials (CRTs) with right-truncated Poisson-distributed outcomes: a motivating example from a malaria vector control trial
BACKGROUND: Cluster randomized trials (CRTs) are increasingly used to study the efficacy of interventions targeted at the population level. Formulae exist to calculate sample sizes for CRTs, but they assume that the domain of the outcomes being considered covers the full range of values of the consi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7394957/ https://www.ncbi.nlm.nih.gov/pubmed/32011684 http://dx.doi.org/10.1093/ije/dyz277 |
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author | Mwandigha, Lazaro M Fraser, Keith J Racine-Poon, Amy Mouksassi, Mohamad-Samer Ghani, Azra C |
author_facet | Mwandigha, Lazaro M Fraser, Keith J Racine-Poon, Amy Mouksassi, Mohamad-Samer Ghani, Azra C |
author_sort | Mwandigha, Lazaro M |
collection | PubMed |
description | BACKGROUND: Cluster randomized trials (CRTs) are increasingly used to study the efficacy of interventions targeted at the population level. Formulae exist to calculate sample sizes for CRTs, but they assume that the domain of the outcomes being considered covers the full range of values of the considered distribution. This assumption is frequently incorrect in epidemiological trials in which counts of infection episodes are right-truncated due to practical constraints on the number of times a person can be tested. METHODS: Motivated by a malaria vector control trial with right-truncated Poisson-distributed outcomes, we investigated the effect of right-truncation on power using Monte Carlo simulations. RESULTS: The results demonstrate that the adverse impact of right-truncation is directly proportional to the magnitude of the event rate, λ, with calculations of power being overestimated in instances where right-truncation was not accounted for. The severity of the adverse impact of right-truncation on power was more pronounced when the number of clusters was ≤30 but decreased the further the right-truncation point was from zero. CONCLUSIONS: Potential right-truncation should always be accounted for in the calculation of sample size requirements at the study design stage. |
format | Online Article Text |
id | pubmed-7394957 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-73949572020-08-04 Power calculations for cluster randomized trials (CRTs) with right-truncated Poisson-distributed outcomes: a motivating example from a malaria vector control trial Mwandigha, Lazaro M Fraser, Keith J Racine-Poon, Amy Mouksassi, Mohamad-Samer Ghani, Azra C Int J Epidemiol Methods BACKGROUND: Cluster randomized trials (CRTs) are increasingly used to study the efficacy of interventions targeted at the population level. Formulae exist to calculate sample sizes for CRTs, but they assume that the domain of the outcomes being considered covers the full range of values of the considered distribution. This assumption is frequently incorrect in epidemiological trials in which counts of infection episodes are right-truncated due to practical constraints on the number of times a person can be tested. METHODS: Motivated by a malaria vector control trial with right-truncated Poisson-distributed outcomes, we investigated the effect of right-truncation on power using Monte Carlo simulations. RESULTS: The results demonstrate that the adverse impact of right-truncation is directly proportional to the magnitude of the event rate, λ, with calculations of power being overestimated in instances where right-truncation was not accounted for. The severity of the adverse impact of right-truncation on power was more pronounced when the number of clusters was ≤30 but decreased the further the right-truncation point was from zero. CONCLUSIONS: Potential right-truncation should always be accounted for in the calculation of sample size requirements at the study design stage. Oxford University Press 2020-06 2020-02-03 /pmc/articles/PMC7394957/ /pubmed/32011684 http://dx.doi.org/10.1093/ije/dyz277 Text en © The Author(s) 2020. 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 Mwandigha, Lazaro M Fraser, Keith J Racine-Poon, Amy Mouksassi, Mohamad-Samer Ghani, Azra C Power calculations for cluster randomized trials (CRTs) with right-truncated Poisson-distributed outcomes: a motivating example from a malaria vector control trial |
title | Power calculations for cluster randomized trials (CRTs) with right-truncated Poisson-distributed outcomes: a motivating example from a malaria vector control trial |
title_full | Power calculations for cluster randomized trials (CRTs) with right-truncated Poisson-distributed outcomes: a motivating example from a malaria vector control trial |
title_fullStr | Power calculations for cluster randomized trials (CRTs) with right-truncated Poisson-distributed outcomes: a motivating example from a malaria vector control trial |
title_full_unstemmed | Power calculations for cluster randomized trials (CRTs) with right-truncated Poisson-distributed outcomes: a motivating example from a malaria vector control trial |
title_short | Power calculations for cluster randomized trials (CRTs) with right-truncated Poisson-distributed outcomes: a motivating example from a malaria vector control trial |
title_sort | power calculations for cluster randomized trials (crts) with right-truncated poisson-distributed outcomes: a motivating example from a malaria vector control trial |
topic | Methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7394957/ https://www.ncbi.nlm.nih.gov/pubmed/32011684 http://dx.doi.org/10.1093/ije/dyz277 |
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