Reporting of statistical regression analyses in Biomédica: A critical assessment review
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...
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doaj-ee55cc9421da4cb0aee7b2fd7397a2202020-11-25T01:32:45ZengInstituto Nacional de SaludBiomédica: revista del Instituto Nacional de Salud0120-41570120-41572018-06-0138217317910.7705/biomedica.v38i0.36482084Reporting of statistical regression analyses in Biomédica: A critical assessment reviewJulián Alfredo Fernández-Niño0Rosa Ivonne Hernández-Montes1Laura Andrea Rodríguez-Villamizar2Departamento de Salud Pública, Facultad de Salud, Universidad Industrial de Santander, Bucaramanga, ColombiaEscuela de Salud Pública de México, Instituto Nacional de Salud Pública, Cuernavaca, MéxicoDepartamento de Salud Pública, Facultad de Salud, Universidad Industrial de Santander, Bucaramanga, ColombiaIntroduction: 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.https://www.revistabiomedica.org/index.php/biomedica/article/view/3648bioestadísticaanálisis de datosanálisis de regresiónsesgo (epidemiología)Colombia |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Julián Alfredo Fernández-Niño Rosa Ivonne Hernández-Montes Laura Andrea Rodríguez-Villamizar |
spellingShingle |
Julián Alfredo Fernández-Niño Rosa Ivonne Hernández-Montes Laura Andrea Rodríguez-Villamizar Reporting of statistical regression analyses in Biomédica: A critical assessment review Biomédica: revista del Instituto Nacional de Salud bioestadística análisis de datos análisis de regresión sesgo (epidemiología) Colombia |
author_facet |
Julián Alfredo Fernández-Niño Rosa Ivonne Hernández-Montes Laura Andrea Rodríguez-Villamizar |
author_sort |
Julián Alfredo Fernández-Niño |
title |
Reporting of statistical regression analyses in Biomédica: A critical assessment review |
title_short |
Reporting of statistical regression analyses in Biomédica: A critical assessment review |
title_full |
Reporting of statistical regression analyses in Biomédica: A critical assessment review |
title_fullStr |
Reporting of statistical regression analyses in Biomédica: A critical assessment review |
title_full_unstemmed |
Reporting of statistical regression analyses in Biomédica: A critical assessment review |
title_sort |
reporting of statistical regression analyses in biomédica: a critical assessment review |
publisher |
Instituto Nacional de Salud |
series |
Biomédica: revista del Instituto Nacional de Salud |
issn |
0120-4157 0120-4157 |
publishDate |
2018-06-01 |
description |
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. |
topic |
bioestadística análisis de datos análisis de regresión sesgo (epidemiología) Colombia |
url |
https://www.revistabiomedica.org/index.php/biomedica/article/view/3648 |
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AT julianalfredofernandeznino reportingofstatisticalregressionanalysesinbiomedicaacriticalassessmentreview AT rosaivonnehernandezmontes reportingofstatisticalregressionanalysesinbiomedicaacriticalassessmentreview AT lauraandrearodriguezvillamizar reportingofstatisticalregressionanalysesinbiomedicaacriticalassessmentreview |
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