Ensuring Causal, Not Casual, Inference

Research output: Contribution to journalArticle

Abstract

With innovation in causal inference methods and a rise in non-experimental data availability, a growing number of prevention researchers and advocates are thinking about causal inference. In this commentary, we discuss the current state of science as it relates to causal inference in prevention research, and reflect on key assumptions of these methods. We review challenges associated with the use of causal inference methodology, as well as considerations for hoping to integrate causal inference methods into their research. In short, this commentary addresses the key concepts of causal inference and suggests a greater emphasis on thoughtfully designed studies (to avoid the need for strong and potentially untestable assumptions) combined with analyses of sensitivity to those assumptions.

Original languageEnglish (US)
Pages (from-to)452-456
Number of pages5
JournalPrevention Science
Volume20
Issue number3
DOIs
StatePublished - Apr 15 2019

Keywords

  • Assumptions
  • Causal inference
  • Mediation
  • Randomized controlled trials

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health

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