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| Format: | Artículo científico |
| Language: | en |
| Published: |
Medical Education Cooperation with Cuba
2017
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| Online Access: | https://www.redalyc.org/articulo.oa?id=437552190012 |
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| _version_ | 1866815009813692416 |
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| author | Vielka González-Ferrer |
| author_facet | Vielka González-Ferrer |
| contents | Statistical Modeling in Health Research: Purpose Drives Approach Vielka González-Ferrer Yainedy González-Ferrer Marcos Ramírez-Marino Medicina Cuba Prognosis causality risk factor linear models tatistical modeling is commonly used in both predictive and ex- planatory studies in health research. Its use in Cuba continues to grow, although it is sometimes employed inappropriately, which can lead to errors that imperil validity. This article attempts to shed light on faulty practices in statistical modeling by examining and discussing the main differences between explanatory and pre- dictive models, with reference to the following: study objectives, theoretical considerations in model-building, aspects requiring assessment, variable and algorithm selection, analysis of con- founders, treatment of multicollinearity, and reporting results. 2017 artículo científico 1555-7960 https://www.redalyc.org/articulo.oa?id=437552190012 en http://www.redalyc.org/revista.oa?id=4375 MEDICC Review application/pdf Medical Education Cooperation with Cuba MEDICC Review (Estados Unidos de América) Num.2-3 Vol.19 |
| format | Artículo científico |
| id | redalyc_437552190012 |
| language | en |
| publishDate | 2017 |
| publisher | Medical Education Cooperation with Cuba |
| spellingShingle | Statistical Modeling in Health Research: Purpose Drives Approach Vielka González-Ferrer Medicina Cuba Prognosis causality risk factor linear models Statistical Modeling in Health Research: Purpose Drives Approach Vielka González-Ferrer Yainedy González-Ferrer Marcos Ramírez-Marino Medicina Cuba Prognosis causality risk factor linear models tatistical modeling is commonly used in both predictive and ex- planatory studies in health research. Its use in Cuba continues to grow, although it is sometimes employed inappropriately, which can lead to errors that imperil validity. This article attempts to shed light on faulty practices in statistical modeling by examining and discussing the main differences between explanatory and pre- dictive models, with reference to the following: study objectives, theoretical considerations in model-building, aspects requiring assessment, variable and algorithm selection, analysis of con- founders, treatment of multicollinearity, and reporting results. 2017 artículo científico 1555-7960 https://www.redalyc.org/articulo.oa?id=437552190012 en http://www.redalyc.org/revista.oa?id=4375 MEDICC Review application/pdf Medical Education Cooperation with Cuba MEDICC Review (Estados Unidos de América) Num.2-3 Vol.19 |
| title | Statistical Modeling in Health Research: Purpose Drives Approach |
| topic | Medicina Cuba Prognosis causality risk factor linear models |
| url | https://www.redalyc.org/articulo.oa?id=437552190012 |