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Assessment of risk of bias in translational science
Risk of bias in translational medicine may take one of three forms: A. a systematic error of methodology as it pertains to measurement or sampling (e.g., selection bias), B. a systematic defect of design that leads to estimates of experimental and control groups, and of effect sizes that substantial...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3751044/ https://www.ncbi.nlm.nih.gov/pubmed/23927081 http://dx.doi.org/10.1186/1479-5876-11-184 |
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author | Barkhordarian, Andre Pellionisz, Peter Dousti, Mona Lam, Vivian Gleason, Lauren Dousti, Mahsa Moura, Josemar Chiappelli, Francesco |
author_facet | Barkhordarian, Andre Pellionisz, Peter Dousti, Mona Lam, Vivian Gleason, Lauren Dousti, Mahsa Moura, Josemar Chiappelli, Francesco |
author_sort | Barkhordarian, Andre |
collection | PubMed |
description | Risk of bias in translational medicine may take one of three forms: A. a systematic error of methodology as it pertains to measurement or sampling (e.g., selection bias), B. a systematic defect of design that leads to estimates of experimental and control groups, and of effect sizes that substantially deviate from true values (e.g., information bias), and C. a systematic distortion of the analytical process, which results in a misrepresentation of the data with consequential errors of inference (e.g., inferential bias). Risk of bias can seriously adulterate the internal and the external validity of a clinical study, and, unless it is identified and systematically evaluated, can seriously hamper the process of comparative effectiveness and efficacy research and analysis for practice. The Cochrane Group and the Agency for Healthcare Research and Quality have independently developed instruments for assessing the meta-construct of risk of bias. The present article begins to discuss this dialectic. |
format | Online Article Text |
id | pubmed-3751044 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-37510442013-08-24 Assessment of risk of bias in translational science Barkhordarian, Andre Pellionisz, Peter Dousti, Mona Lam, Vivian Gleason, Lauren Dousti, Mahsa Moura, Josemar Chiappelli, Francesco J Transl Med Editorial Risk of bias in translational medicine may take one of three forms: A. a systematic error of methodology as it pertains to measurement or sampling (e.g., selection bias), B. a systematic defect of design that leads to estimates of experimental and control groups, and of effect sizes that substantially deviate from true values (e.g., information bias), and C. a systematic distortion of the analytical process, which results in a misrepresentation of the data with consequential errors of inference (e.g., inferential bias). Risk of bias can seriously adulterate the internal and the external validity of a clinical study, and, unless it is identified and systematically evaluated, can seriously hamper the process of comparative effectiveness and efficacy research and analysis for practice. The Cochrane Group and the Agency for Healthcare Research and Quality have independently developed instruments for assessing the meta-construct of risk of bias. The present article begins to discuss this dialectic. BioMed Central 2013-08-08 /pmc/articles/PMC3751044/ /pubmed/23927081 http://dx.doi.org/10.1186/1479-5876-11-184 Text en Copyright © 2013 Barkhordarian et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Editorial Barkhordarian, Andre Pellionisz, Peter Dousti, Mona Lam, Vivian Gleason, Lauren Dousti, Mahsa Moura, Josemar Chiappelli, Francesco Assessment of risk of bias in translational science |
title | Assessment of risk of bias in translational science |
title_full | Assessment of risk of bias in translational science |
title_fullStr | Assessment of risk of bias in translational science |
title_full_unstemmed | Assessment of risk of bias in translational science |
title_short | Assessment of risk of bias in translational science |
title_sort | assessment of risk of bias in translational science |
topic | Editorial |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3751044/ https://www.ncbi.nlm.nih.gov/pubmed/23927081 http://dx.doi.org/10.1186/1479-5876-11-184 |
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