• Media type: E-Article
  • Title: A Systematic Statistical Approach to Evaluating Evidence from Observational Studies
  • Contributor: Madigan, David; Stang, Paul E.; Berlin, Jesse A.; Schuemie, Martijn; Overhage, J. Marc; Suchard, Marc A.; Dumouchel, Bill; Hartzema, Abraham G.; Ryan, Patrick B.
  • imprint: Annual Reviews, 2014
  • Published in: Annual Review of Statistics and Its Application
  • Language: English
  • DOI: 10.1146/annurev-statistics-022513-115645
  • ISSN: 2326-8298; 2326-831X
  • Keywords: Statistics, Probability and Uncertainty ; Statistics and Probability
  • Origination:
  • Footnote:
  • Description: <jats:p> Threats to the validity of observational studies on the effects of interventions raise questions about the appropriate role of such studies in decision making. Nonetheless, scholarly journals in fields such as medicine, education, and the social sciences feature many such studies, often with limited exploration of these threats, and the lay press is rife with news stories based on these studies. Consumers of these studies rely on the expertise of the study authors to conduct appropriate analyses, and on the thoroughness of the scientific peer-review process to check the validity, but the introspective and ad hoc nature of the design of these analyses appears to elude any meaningful objective assessment of their performance. Here, we review some of the challenges encountered in observational studies and review an alternative, data-driven approach to observational study design, execution, and analysis. Although much work remains, we believe this research direction shows promise. </jats:p>