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Assessment of P values for demographic data in randomized controlled trials
In a large number of randomized controlled trials, researchers provide P values for demographic data, which are commonly reported in table 1 of the article for the purpose of emphasizing the lack of differences between or among groups. As such, the authors intend to demonstrate that statistically in...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Society of Anesthesiologists
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6458506/ https://www.ncbi.nlm.nih.gov/pubmed/30518168 http://dx.doi.org/10.4097/kja.d.18.00333 |
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author | Ahn, Eun Jin Kim, Jong Hae Kim, Tae Kyun Park, Jae Hong Lee, Dong Kyu Lee, Sangseok In, Junyong Kang, Hyun |
author_facet | Ahn, Eun Jin Kim, Jong Hae Kim, Tae Kyun Park, Jae Hong Lee, Dong Kyu Lee, Sangseok In, Junyong Kang, Hyun |
author_sort | Ahn, Eun Jin |
collection | PubMed |
description | In a large number of randomized controlled trials, researchers provide P values for demographic data, which are commonly reported in table 1 of the article for the purpose of emphasizing the lack of differences between or among groups. As such, the authors intend to demonstrate that statistically insignificant P values in the demographic data confirm that group randomization was adequately performed. However, statistically insignificant P values do not necessarily reflect successful randomization. It is more important to rigorously establish a plan for statistical analysis during the design and planning stage of the study, and to consider whether any of the variables included in the demographic data could potentially affect the research results. If a researcher rigorously designed and planned a study, and performed it accordingly, the conclusions drawn from the results would not be influenced by P values, regardless of whether they were significant. In contrasts, imbalanced variables could affect the results after variance controlling, even though whole study process are well planned and executed. In this situation, the researcher can provide results with both the initial method and a second stage of analysis including such variables. Otherwise, for brief conclusions, it would be pointless to report P values in a table simply listing baseline data of the participants. |
format | Online Article Text |
id | pubmed-6458506 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Korean Society of Anesthesiologists |
record_format | MEDLINE/PubMed |
spelling | pubmed-64585062019-04-19 Assessment of P values for demographic data in randomized controlled trials Ahn, Eun Jin Kim, Jong Hae Kim, Tae Kyun Park, Jae Hong Lee, Dong Kyu Lee, Sangseok In, Junyong Kang, Hyun Korean J Anesthesiol Statistical Round In a large number of randomized controlled trials, researchers provide P values for demographic data, which are commonly reported in table 1 of the article for the purpose of emphasizing the lack of differences between or among groups. As such, the authors intend to demonstrate that statistically insignificant P values in the demographic data confirm that group randomization was adequately performed. However, statistically insignificant P values do not necessarily reflect successful randomization. It is more important to rigorously establish a plan for statistical analysis during the design and planning stage of the study, and to consider whether any of the variables included in the demographic data could potentially affect the research results. If a researcher rigorously designed and planned a study, and performed it accordingly, the conclusions drawn from the results would not be influenced by P values, regardless of whether they were significant. In contrasts, imbalanced variables could affect the results after variance controlling, even though whole study process are well planned and executed. In this situation, the researcher can provide results with both the initial method and a second stage of analysis including such variables. Otherwise, for brief conclusions, it would be pointless to report P values in a table simply listing baseline data of the participants. Korean Society of Anesthesiologists 2019-04 2018-12-06 /pmc/articles/PMC6458506/ /pubmed/30518168 http://dx.doi.org/10.4097/kja.d.18.00333 Text en Copyright © The Korean Society of Anesthesiologists, 2019 This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Statistical Round Ahn, Eun Jin Kim, Jong Hae Kim, Tae Kyun Park, Jae Hong Lee, Dong Kyu Lee, Sangseok In, Junyong Kang, Hyun Assessment of P values for demographic data in randomized controlled trials |
title | Assessment of P values for demographic data in randomized controlled trials |
title_full | Assessment of P values for demographic data in randomized controlled trials |
title_fullStr | Assessment of P values for demographic data in randomized controlled trials |
title_full_unstemmed | Assessment of P values for demographic data in randomized controlled trials |
title_short | Assessment of P values for demographic data in randomized controlled trials |
title_sort | assessment of p values for demographic data in randomized controlled trials |
topic | Statistical Round |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6458506/ https://www.ncbi.nlm.nih.gov/pubmed/30518168 http://dx.doi.org/10.4097/kja.d.18.00333 |
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