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A review for clinical outcomes research: hypothesis generation, data strategy, and hypothesis-driven statistical analysis
In recent years, more and more large, population-level databases have become available for clinical research. The size and complexity of these databases often present a methodological challenge for investigators. We propose that a “protocol” may facilitate the research process using these databases....
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer-Verlag
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3116115/ https://www.ncbi.nlm.nih.gov/pubmed/21359904 http://dx.doi.org/10.1007/s00464-010-1543-7 |
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author | Chang, David C. Talamini, Mark A. |
author_facet | Chang, David C. Talamini, Mark A. |
author_sort | Chang, David C. |
collection | PubMed |
description | In recent years, more and more large, population-level databases have become available for clinical research. The size and complexity of these databases often present a methodological challenge for investigators. We propose that a “protocol” may facilitate the research process using these databases. In addition, much like the structured History and Physical (H&P) helps the audience appreciate the details of a patient case more systematically, a formal outcomes research protocol can also help in the systematic evaluation of an outcomes research manuscript. |
format | Online Article Text |
id | pubmed-3116115 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Springer-Verlag |
record_format | MEDLINE/PubMed |
spelling | pubmed-31161152011-07-14 A review for clinical outcomes research: hypothesis generation, data strategy, and hypothesis-driven statistical analysis Chang, David C. Talamini, Mark A. Surg Endosc Article In recent years, more and more large, population-level databases have become available for clinical research. The size and complexity of these databases often present a methodological challenge for investigators. We propose that a “protocol” may facilitate the research process using these databases. In addition, much like the structured History and Physical (H&P) helps the audience appreciate the details of a patient case more systematically, a formal outcomes research protocol can also help in the systematic evaluation of an outcomes research manuscript. Springer-Verlag 2011-02-27 2011 /pmc/articles/PMC3116115/ /pubmed/21359904 http://dx.doi.org/10.1007/s00464-010-1543-7 Text en © The Author(s) 2011 https://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. |
spellingShingle | Article Chang, David C. Talamini, Mark A. A review for clinical outcomes research: hypothesis generation, data strategy, and hypothesis-driven statistical analysis |
title | A review for clinical outcomes research: hypothesis generation, data strategy, and hypothesis-driven statistical analysis |
title_full | A review for clinical outcomes research: hypothesis generation, data strategy, and hypothesis-driven statistical analysis |
title_fullStr | A review for clinical outcomes research: hypothesis generation, data strategy, and hypothesis-driven statistical analysis |
title_full_unstemmed | A review for clinical outcomes research: hypothesis generation, data strategy, and hypothesis-driven statistical analysis |
title_short | A review for clinical outcomes research: hypothesis generation, data strategy, and hypothesis-driven statistical analysis |
title_sort | review for clinical outcomes research: hypothesis generation, data strategy, and hypothesis-driven statistical analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3116115/ https://www.ncbi.nlm.nih.gov/pubmed/21359904 http://dx.doi.org/10.1007/s00464-010-1543-7 |
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