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Variable selection: current practice in epidemiological studies

Selection of covariates is among the most controversial and difficult tasks in epidemiologic analysis. Correct variable selection addresses the problem of confounding in etiologic research and allows unbiased estimation of probabilities in prognostic studies. The aim of this commentary is to assess...

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Detalles Bibliográficos
Autores principales: Walter, Stefan, Tiemeier, Henning
Formato: Texto
Lenguaje:English
Publicado: Springer Netherlands 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2791468/
https://www.ncbi.nlm.nih.gov/pubmed/19967429
http://dx.doi.org/10.1007/s10654-009-9411-2
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author Walter, Stefan
Tiemeier, Henning
author_facet Walter, Stefan
Tiemeier, Henning
author_sort Walter, Stefan
collection PubMed
description Selection of covariates is among the most controversial and difficult tasks in epidemiologic analysis. Correct variable selection addresses the problem of confounding in etiologic research and allows unbiased estimation of probabilities in prognostic studies. The aim of this commentary is to assess how often different variable selection techniques were applied in contemporary epidemiologic analysis. It was of particular interest to see whether modern methods such as shrinkage or penalized regression were used in recent publications. Stepwise selection methods remained the predominant method for variable selection in publications in epidemiological journals in 2008. Shrinkage methods were not used in any of the reviewed articles. Editors, reviewers and authors have insufficiently promoted the new, less controversial approaches of variable selection in the biomedical literature, whereas statisticians may not have adequately addressed the method’s feasibility.
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spelling pubmed-27914682009-12-15 Variable selection: current practice in epidemiological studies Walter, Stefan Tiemeier, Henning Eur J Epidemiol Commentary Selection of covariates is among the most controversial and difficult tasks in epidemiologic analysis. Correct variable selection addresses the problem of confounding in etiologic research and allows unbiased estimation of probabilities in prognostic studies. The aim of this commentary is to assess how often different variable selection techniques were applied in contemporary epidemiologic analysis. It was of particular interest to see whether modern methods such as shrinkage or penalized regression were used in recent publications. Stepwise selection methods remained the predominant method for variable selection in publications in epidemiological journals in 2008. Shrinkage methods were not used in any of the reviewed articles. Editors, reviewers and authors have insufficiently promoted the new, less controversial approaches of variable selection in the biomedical literature, whereas statisticians may not have adequately addressed the method’s feasibility. Springer Netherlands 2009-12-05 2009 /pmc/articles/PMC2791468/ /pubmed/19967429 http://dx.doi.org/10.1007/s10654-009-9411-2 Text en © The Author(s) 2009 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 Commentary
Walter, Stefan
Tiemeier, Henning
Variable selection: current practice in epidemiological studies
title Variable selection: current practice in epidemiological studies
title_full Variable selection: current practice in epidemiological studies
title_fullStr Variable selection: current practice in epidemiological studies
title_full_unstemmed Variable selection: current practice in epidemiological studies
title_short Variable selection: current practice in epidemiological studies
title_sort variable selection: current practice in epidemiological studies
topic Commentary
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2791468/
https://www.ncbi.nlm.nih.gov/pubmed/19967429
http://dx.doi.org/10.1007/s10654-009-9411-2
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