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Understanding Variation in Sets of N-of-1 Trials
A recent paper in this journal by Chen and Chen has used computer simulations to examine a number of approaches to analysing sets of n-of-1 trials. We have examined such designs using a more theoretical approach based on considering the purpose of analysis and the structure as regards randomisation...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5131970/ https://www.ncbi.nlm.nih.gov/pubmed/27907056 http://dx.doi.org/10.1371/journal.pone.0167167 |
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author | Araujo, Artur Julious, Steven Senn, Stephen |
author_facet | Araujo, Artur Julious, Steven Senn, Stephen |
author_sort | Araujo, Artur |
collection | PubMed |
description | A recent paper in this journal by Chen and Chen has used computer simulations to examine a number of approaches to analysing sets of n-of-1 trials. We have examined such designs using a more theoretical approach based on considering the purpose of analysis and the structure as regards randomisation that the design uses. We show that different purposes require different analyses and that these in turn may produce quite different results. Our approach to incorporating the randomisation employed when the purpose is to test a null hypothesis of strict equality of the treatment makes use of Nelder’s theory of general balance. However, where the purpose is to make inferences about the effects for individual patients, we show that a mixed model is needed. There are strong parallels to the difference between fixed and random effects meta-analyses and these are discussed. |
format | Online Article Text |
id | pubmed-5131970 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-51319702016-12-21 Understanding Variation in Sets of N-of-1 Trials Araujo, Artur Julious, Steven Senn, Stephen PLoS One Research Article A recent paper in this journal by Chen and Chen has used computer simulations to examine a number of approaches to analysing sets of n-of-1 trials. We have examined such designs using a more theoretical approach based on considering the purpose of analysis and the structure as regards randomisation that the design uses. We show that different purposes require different analyses and that these in turn may produce quite different results. Our approach to incorporating the randomisation employed when the purpose is to test a null hypothesis of strict equality of the treatment makes use of Nelder’s theory of general balance. However, where the purpose is to make inferences about the effects for individual patients, we show that a mixed model is needed. There are strong parallels to the difference between fixed and random effects meta-analyses and these are discussed. Public Library of Science 2016-12-01 /pmc/articles/PMC5131970/ /pubmed/27907056 http://dx.doi.org/10.1371/journal.pone.0167167 Text en © 2016 Araujo 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 Araujo, Artur Julious, Steven Senn, Stephen Understanding Variation in Sets of N-of-1 Trials |
title | Understanding Variation in Sets of N-of-1 Trials |
title_full | Understanding Variation in Sets of N-of-1 Trials |
title_fullStr | Understanding Variation in Sets of N-of-1 Trials |
title_full_unstemmed | Understanding Variation in Sets of N-of-1 Trials |
title_short | Understanding Variation in Sets of N-of-1 Trials |
title_sort | understanding variation in sets of n-of-1 trials |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5131970/ https://www.ncbi.nlm.nih.gov/pubmed/27907056 http://dx.doi.org/10.1371/journal.pone.0167167 |
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