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Directed Acyclic Graphs: Alternative tool for causal inference in epidemiology and biostatistics research and teaching

  • Tran Ngoc Dang, Khuong Quynh Long, Huynh Thi Hong Tram, Le Huynh Thi Cam Hong, Tuan Minh Vo,
  • Pages 12-16
  • 27/10/2018
  • 123
  • 292
  • Free

The issue of causation is one of the major challenges for epidemiologists who aim to understand the association between an exposure and an outcome to explain disease patterns and potentially provide a basis for intervention. Suitably designed experimental studies can offer robust evidence of the causal relationships. The experimental studies, however, are not popular, difficult or even unethical and impossible to conduct; it would be desirable if there is a methodology for reducing bias or strengthening the causal inferences drawn from observational studies. The traditional approach of estimating causal effects in such studies is to adjust for a set of variables judged to be confounders by including them in a multiple regression. However, which variables should be adjusted for as confounders in a regression model has long been a controversial issue in epidemiology. From my observation, the adjustments using only "statistical artifacts" methods such as the p-value<0.2 in univariate analysis, stepwise (forward/backward) are widely used in research and teaching in Epidemiology and Statistics but without appropriated notice on the biological or clinical relationships between exposure and outcome which may induce the bias in estimating causal effects. In this mini-review, we introduce an interesting method, namely Directed Acyclic Graphs (DAGs), which can be used to reduce the bias in estimating causal effects; it is also a good application for Epidemiology and Biostatistics teaching.

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Evidence-based medicine education improve clinical knowledge of 4th year medical students in the university of medicine and pharmacy at Ho Chi Minh City

Letter to Editor
  • Tuan Minh Vo, Thang Bui Quoc, Dat Van Truong,
  • Pages 17-19

Evidence based medicine (EBM) education is a modern method for medical students in clinical training based on the reasonable use of the best evidence in making decisions about individual patient’s treatment. EBM education syllabus teaches medical student how to integrate the clinical experience and patient examination with the simplest out-there analysis data for increasing the utilization of top quality clinical analysis in clinical deciding, this methodology requires new literature looking out and proof evaluating skills. Thus, replacing the recently educated method by EBM has more challenges, the new program ought to analysis fastidiously for evaluating the behavior changes, the development of clinical skills and analysis the ultimate examination score for evaluating the effectiveness of EBM program. The result show that active teaching proves to be statistically completely different and has robust impact toward the ultimate outcome. EBM educated method might improve clinical knowledge and application of PBL/EBM brings concerning higher scores compared to recently educated method.

Graphical abstract