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Mixed effects approach to the analysis of the stepped wedge cluster randomised trial—Investigating the confounding effect of time through simulation
BACKGROUND: A stepped wedge cluster randomised trial (SWCRT) is a multicentred study which allows an intervention to be rolled out at sites in a random order. Once the intervention is initiated at a site, all participants within that site remain exposed to the intervention for the remainder of the s...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6292598/ https://www.ncbi.nlm.nih.gov/pubmed/30543671 http://dx.doi.org/10.1371/journal.pone.0208876 |
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author | Nickless, Alecia Voysey, Merryn Geddes, John Yu, Ly-Mee Fanshawe, Thomas R. |
author_facet | Nickless, Alecia Voysey, Merryn Geddes, John Yu, Ly-Mee Fanshawe, Thomas R. |
author_sort | Nickless, Alecia |
collection | PubMed |
description | BACKGROUND: A stepped wedge cluster randomised trial (SWCRT) is a multicentred study which allows an intervention to be rolled out at sites in a random order. Once the intervention is initiated at a site, all participants within that site remain exposed to the intervention for the remainder of the study. The time since the start of the study (“calendar time”) may affect outcome measures through underlying time trends or periodicity. The time since the intervention was introduced to a site (“exposure time”) may also affect outcomes cumulatively for successful interventions, possibly in addition to a step change when the intervention began. METHODS: Motivated by a SWCRT of self-monitoring for bipolar disorder, we conducted a simulation study to compare model formulations to analyse data from a SWCRT under 36 different scenarios in which time was related to the outcome (improvement in mood score). The aim was to find a model specification that would produce reliable estimates of intervention effects under different scenarios. Nine different formulations of a linear mixed effects model were fitted to these datasets. These models varied in the specification of calendar and exposure times. RESULTS: Modelling the effects of the intervention was best accomplished by including terms for both calendar time and exposure time. Treating time as categorical (a separate parameter for each measurement time-step) achieved the best coverage probabilities and low bias, but at a cost of wider confidence intervals compared to simpler models for those scenarios which were sufficiently modelled by fewer parameters. Treating time as continuous and including a quadratic time term performed similarly well, with slightly larger variations in coverage probability, but narrower confidence intervals and in some cases lower bias. The impact of misspecifying the covariance structure was comparatively small. CONCLUSIONS: We recommend that unless there is a priori information to indicate the form of the relationship between time and outcomes, data from SWCRTs should be analysed with a linear mixed effects model that includes separate categorical terms for calendar time and exposure time. Prespecified sensitivity analyses should consider the different formulations of these time effects in the model, to assess their impact on estimates of intervention effects. |
format | Online Article Text |
id | pubmed-6292598 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-62925982018-12-28 Mixed effects approach to the analysis of the stepped wedge cluster randomised trial—Investigating the confounding effect of time through simulation Nickless, Alecia Voysey, Merryn Geddes, John Yu, Ly-Mee Fanshawe, Thomas R. PLoS One Research Article BACKGROUND: A stepped wedge cluster randomised trial (SWCRT) is a multicentred study which allows an intervention to be rolled out at sites in a random order. Once the intervention is initiated at a site, all participants within that site remain exposed to the intervention for the remainder of the study. The time since the start of the study (“calendar time”) may affect outcome measures through underlying time trends or periodicity. The time since the intervention was introduced to a site (“exposure time”) may also affect outcomes cumulatively for successful interventions, possibly in addition to a step change when the intervention began. METHODS: Motivated by a SWCRT of self-monitoring for bipolar disorder, we conducted a simulation study to compare model formulations to analyse data from a SWCRT under 36 different scenarios in which time was related to the outcome (improvement in mood score). The aim was to find a model specification that would produce reliable estimates of intervention effects under different scenarios. Nine different formulations of a linear mixed effects model were fitted to these datasets. These models varied in the specification of calendar and exposure times. RESULTS: Modelling the effects of the intervention was best accomplished by including terms for both calendar time and exposure time. Treating time as categorical (a separate parameter for each measurement time-step) achieved the best coverage probabilities and low bias, but at a cost of wider confidence intervals compared to simpler models for those scenarios which were sufficiently modelled by fewer parameters. Treating time as continuous and including a quadratic time term performed similarly well, with slightly larger variations in coverage probability, but narrower confidence intervals and in some cases lower bias. The impact of misspecifying the covariance structure was comparatively small. CONCLUSIONS: We recommend that unless there is a priori information to indicate the form of the relationship between time and outcomes, data from SWCRTs should be analysed with a linear mixed effects model that includes separate categorical terms for calendar time and exposure time. Prespecified sensitivity analyses should consider the different formulations of these time effects in the model, to assess their impact on estimates of intervention effects. Public Library of Science 2018-12-13 /pmc/articles/PMC6292598/ /pubmed/30543671 http://dx.doi.org/10.1371/journal.pone.0208876 Text en © 2018 Nickless et al 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 author and source are credited. |
spellingShingle | Research Article Nickless, Alecia Voysey, Merryn Geddes, John Yu, Ly-Mee Fanshawe, Thomas R. Mixed effects approach to the analysis of the stepped wedge cluster randomised trial—Investigating the confounding effect of time through simulation |
title | Mixed effects approach to the analysis of the stepped wedge cluster randomised trial—Investigating the confounding effect of time through simulation |
title_full | Mixed effects approach to the analysis of the stepped wedge cluster randomised trial—Investigating the confounding effect of time through simulation |
title_fullStr | Mixed effects approach to the analysis of the stepped wedge cluster randomised trial—Investigating the confounding effect of time through simulation |
title_full_unstemmed | Mixed effects approach to the analysis of the stepped wedge cluster randomised trial—Investigating the confounding effect of time through simulation |
title_short | Mixed effects approach to the analysis of the stepped wedge cluster randomised trial—Investigating the confounding effect of time through simulation |
title_sort | mixed effects approach to the analysis of the stepped wedge cluster randomised trial—investigating the confounding effect of time through simulation |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6292598/ https://www.ncbi.nlm.nih.gov/pubmed/30543671 http://dx.doi.org/10.1371/journal.pone.0208876 |
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