A Future for Observational Epidemiology: Clarity, Credibility, Transparency. Issue 5 (16th March 2019)

• Record Type: Journal Article
• Authors: Harper, Sam
• Is Part Of: American journal of epidemiology. Volume 188:Issue 5(2019)
• Page Start: 840
• Page End: 845
• Publication Date: 2019-03-16
• Subjects: causal inference -- observational studies -- quantitative bias analysis -- quasi-experiments -- reproducible research -- research reporting -- transparency; Epidemiology -- Periodicals; Public health -- Periodicals; 614.4
• DOI: 10.1093/aje/kwy280
• Languages: English
• ISSNs: 0002-9262

Abstract

Abstract: Observational studies are ambiguous, difficult, and necessary for epidemiology. Presently, there are concerns that the evidence produced by most observational studies in epidemiology is not credible and contributes to research waste. I argue that observational epidemiology could be improved by focusing greater attention on 1) defining questions that make clear whether the inferential goal is descriptive or causal; 2) greater utilization of quantitative bias analysis and alternative research designs that aim to decrease the strength of assumptions needed to estimate causal effects; and 3) promoting, experimenting with, and perhaps institutionalizing both reproducible research standards and replication studies to evaluate the fragility of study findings in epidemiology. Greater clarity, credibility, and transparency in observational epidemiology will help to provide reliable evidence that can serve as a basis for making decisions about clinical or population-health interventions.