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Dichotomizing partial compliance and increased participant burden in factorial designs: the performance of four noncompliance methods
BACKGROUND: Noncompliance to treatment assignment is an inevitable occurrence in randomized clinical trials (RCTs). Intention to treat (ITT) is generally considered the best method for addressing noncompliance in RCTs. Alternatives to ITT exist, including per protocol (PP), as treated (AT), and inst...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4647702/ https://www.ncbi.nlm.nih.gov/pubmed/26573840 http://dx.doi.org/10.1186/s13063-015-1044-z |
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author | Merrill, Peter D. McClure, Leslie A. |
author_facet | Merrill, Peter D. McClure, Leslie A. |
author_sort | Merrill, Peter D. |
collection | PubMed |
description | BACKGROUND: Noncompliance to treatment assignment is an inevitable occurrence in randomized clinical trials (RCTs). Intention to treat (ITT) is generally considered the best method for addressing noncompliance in RCTs. Alternatives to ITT exist, including per protocol (PP), as treated (AT), and instrumental variables (IV). These three methods define participant compliance dichotomously, but partial compliance is a common occurrence in RCTs. By defining a threshold, above which a participant is called a complier, PP, AT and IV can be used, but the resulting loss of information may affect their performance. Trials with factorial designs may experience higher rates of noncompliance due to the heavier burden that participants experience by being assigned to multiple experimental treatments. METHODS: Using simulations, we assessed the performance of ITT, PP, AT, and IV in both the partial compliance setting and in a 2-by-2 factorial design with increased participant burden for those randomized to both active treatments. RESULTS: The bias, mean squared error, and type I error rates of the IV method after dichotomizing partial compliance were heavily inflated. The performance of all four methods depended on the level of noncompliance present, with higher average noncompliance leading to poorer performance. PP and AT showed improved bias and power relative to ITT without inflating the type I error beyond acceptable limits. However, the PP and AT heavily inflated the type I error rates when participant compliance was affected by the participants’ general health. CONCLUSIONS: There are consequences for dichotomizing compliance information to make it fit into well-known methods. The results suggest the need for a method of estimating treatment effects that can utilize partial compliance information. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13063-015-1044-z) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4647702 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-46477022015-11-18 Dichotomizing partial compliance and increased participant burden in factorial designs: the performance of four noncompliance methods Merrill, Peter D. McClure, Leslie A. Trials Research BACKGROUND: Noncompliance to treatment assignment is an inevitable occurrence in randomized clinical trials (RCTs). Intention to treat (ITT) is generally considered the best method for addressing noncompliance in RCTs. Alternatives to ITT exist, including per protocol (PP), as treated (AT), and instrumental variables (IV). These three methods define participant compliance dichotomously, but partial compliance is a common occurrence in RCTs. By defining a threshold, above which a participant is called a complier, PP, AT and IV can be used, but the resulting loss of information may affect their performance. Trials with factorial designs may experience higher rates of noncompliance due to the heavier burden that participants experience by being assigned to multiple experimental treatments. METHODS: Using simulations, we assessed the performance of ITT, PP, AT, and IV in both the partial compliance setting and in a 2-by-2 factorial design with increased participant burden for those randomized to both active treatments. RESULTS: The bias, mean squared error, and type I error rates of the IV method after dichotomizing partial compliance were heavily inflated. The performance of all four methods depended on the level of noncompliance present, with higher average noncompliance leading to poorer performance. PP and AT showed improved bias and power relative to ITT without inflating the type I error beyond acceptable limits. However, the PP and AT heavily inflated the type I error rates when participant compliance was affected by the participants’ general health. CONCLUSIONS: There are consequences for dichotomizing compliance information to make it fit into well-known methods. The results suggest the need for a method of estimating treatment effects that can utilize partial compliance information. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13063-015-1044-z) contains supplementary material, which is available to authorized users. BioMed Central 2015-11-17 /pmc/articles/PMC4647702/ /pubmed/26573840 http://dx.doi.org/10.1186/s13063-015-1044-z Text en © Merrill and McClure. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Merrill, Peter D. McClure, Leslie A. Dichotomizing partial compliance and increased participant burden in factorial designs: the performance of four noncompliance methods |
title | Dichotomizing partial compliance and increased participant burden in factorial designs: the performance of four noncompliance methods |
title_full | Dichotomizing partial compliance and increased participant burden in factorial designs: the performance of four noncompliance methods |
title_fullStr | Dichotomizing partial compliance and increased participant burden in factorial designs: the performance of four noncompliance methods |
title_full_unstemmed | Dichotomizing partial compliance and increased participant burden in factorial designs: the performance of four noncompliance methods |
title_short | Dichotomizing partial compliance and increased participant burden in factorial designs: the performance of four noncompliance methods |
title_sort | dichotomizing partial compliance and increased participant burden in factorial designs: the performance of four noncompliance methods |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4647702/ https://www.ncbi.nlm.nih.gov/pubmed/26573840 http://dx.doi.org/10.1186/s13063-015-1044-z |
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