Reporting of statistical regression analyses in Biomédica: A critical assessment review
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| Format: | Artículo científico |
| Sprache: | en |
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Instituto Nacional de Salud
2018
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| _version_ | 1876463486521835520 |
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| author | Julián Alfredo Fernández-Niño |
| author_facet | Julián Alfredo Fernández-Niño |
| contents | Reporting of statistical regression analyses in Biomédica: A critical assessment review Julián Alfredo Fernández-Niño Rosa Ivonne Hernández-Montes Laura Andrea Rodríguez-Villamizar Medicina Colombia Biostatistics data analysis regression analysis bias (epidemiology) Introduction: Regression modeling is a statistical method commonly used in health research, especially by observational studies.Objective: The objectives of this paper were to 1) determine the frequency of reporting of regression modeling in original biomedical and public health articles that were published in Biomédica between 2000 and 2017; 2) describe the parameters used in the statistical models, and 3) describe the quality of the information reported by the studies to explain the statistical analyses.Materials and methods: We conducted a critical assessment review of all original articles published in Biomédica between 2000 and 2017 that used regression models for the statistical analysis of the studies main objectives. We generated a 20-item checklist based on four good practice guidelines for the presentation of statistical methods. Results: Most of the studies were observational studies related to public health sciences (65.7%). Less than half (37.2%) of them reported using a combination of conceptual frameworks and statistical criteria for the selection of variables to be included in the regression model. Less than one quarter (22.1%) reported the verification of the assumptions of the model. The most frequently used uncertainty measure was the p-value (73.5%).Conclusion: There are significant limitations in the quality of the reports of statistical regression models, which reviewers and readers need in order to correctly assess and interpret the statistical models. The results, herein, are provided as an invitation to researchers, reviewers, and editors of biomedical journals to develop, promote, and control an appropriate culture for statistical analysis and reporting in Colombia. 2018 artículo científico 0120-4157 https://www.redalyc.org/articulo.oa?id=84356684005 https://www.redalyc.org/journal/843/84356684005/ https://www.redalyc.org/journal/843/84356684005/html/ https://www.redalyc.org/journal/843/84356684005/84356684005.epub https://www.redalyc.org/journal/843/84356684005/movil 10.7705/biomedica.v38i0.3648 en http://www.redalyc.org/revista.oa?id=843 Biomédica application/pdf Instituto Nacional de Salud Biomédica (Colombia) Num.2 Vol.38 |
| format | Artículo científico |
| id | redalyc_84356684005 |
| institution | Redalyc |
| language | en |
| publishDate | 2018 |
| publisher | Instituto Nacional de Salud |
| spellingShingle | Reporting of statistical regression analyses in Biomédica: A critical assessment review Julián Alfredo Fernández-Niño Medicina Colombia Biostatistics data analysis regression analysis bias (epidemiology) Reporting of statistical regression analyses in Biomédica: A critical assessment review Julián Alfredo Fernández-Niño Rosa Ivonne Hernández-Montes Laura Andrea Rodríguez-Villamizar Medicina Colombia Biostatistics data analysis regression analysis bias (epidemiology) Introduction: Regression modeling is a statistical method commonly used in health research, especially by observational studies.Objective: The objectives of this paper were to 1) determine the frequency of reporting of regression modeling in original biomedical and public health articles that were published in Biomédica between 2000 and 2017; 2) describe the parameters used in the statistical models, and 3) describe the quality of the information reported by the studies to explain the statistical analyses.Materials and methods: We conducted a critical assessment review of all original articles published in Biomédica between 2000 and 2017 that used regression models for the statistical analysis of the studies main objectives. We generated a 20-item checklist based on four good practice guidelines for the presentation of statistical methods. Results: Most of the studies were observational studies related to public health sciences (65.7%). Less than half (37.2%) of them reported using a combination of conceptual frameworks and statistical criteria for the selection of variables to be included in the regression model. Less than one quarter (22.1%) reported the verification of the assumptions of the model. The most frequently used uncertainty measure was the p-value (73.5%).Conclusion: There are significant limitations in the quality of the reports of statistical regression models, which reviewers and readers need in order to correctly assess and interpret the statistical models. The results, herein, are provided as an invitation to researchers, reviewers, and editors of biomedical journals to develop, promote, and control an appropriate culture for statistical analysis and reporting in Colombia. 2018 artículo científico 0120-4157 https://www.redalyc.org/articulo.oa?id=84356684005 https://www.redalyc.org/journal/843/84356684005/ https://www.redalyc.org/journal/843/84356684005/html/ https://www.redalyc.org/journal/843/84356684005/84356684005.epub https://www.redalyc.org/journal/843/84356684005/movil 10.7705/biomedica.v38i0.3648 en http://www.redalyc.org/revista.oa?id=843 Biomédica application/pdf Instituto Nacional de Salud Biomédica (Colombia) Num.2 Vol.38 |
| title | Reporting of statistical regression analyses in Biomédica: A critical assessment review |
| topic | Medicina Colombia Biostatistics data analysis regression analysis bias (epidemiology) |
| url | https://www.redalyc.org/articulo.oa?id=84356684005 https://www.redalyc.org/journal/843/84356684005/ https://www.redalyc.org/journal/843/84356684005/html/ https://www.redalyc.org/journal/843/84356684005/84356684005.epub https://www.redalyc.org/journal/843/84356684005/movil |