Causal Inference

NOTE: This page describes work that is no longer ongoing at The Methodology Center. We maintain the page because it contains information and materials that may be valuable to researchers. Last updated: August 2015.


The aim of causal inference research is to identify the impact of exposure to a particular treatment or program. Much of the Methodology Center’s work on causal inference focuses on using propensity scores to determine causality in observational studies. This work allows scientists to evaluate health interventions more accurately and will lead to more effective and efficient treatment and prevention of health and social problems.

Introductory Example: How an HIV-Prevention Intervention Works

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The Reducing Risky Relationships HIV (RRR-HIV) intervention was designed to decrease incorrect and dangerous thoughts about relationships in order to reduce risky sexual behavior among women being released from prison. Results showed that women who participated in the program engaged in less unprotected sex.

For future interventions, it is important to determine why this happened. Was it because, as hypothesized, the intervention changed their beliefs about relationships? Was it because the intervention reduced their substance use? Or was it because they bonded with other participants in the intervention? With multiple factors at work, determining the mechanism through which the intervention reduced unprotected sex can be difficult. Using a causal mediation model, scientists can answer these types of questions.

Resources

Recommended reading
Podcast: Using propensity scores

Funding

Our research on causal inference was supported by National Institute of Environmental Health Sciences grant K01 ES025437.
Significant support has been provided by National Institute on Drug Abuse (NIDA) grant P50 DA10075.

Center Methodological & Technical Research

  • Causality in the presence of a mediator
  • Causality in the presence of a moderator
  • Causality in the presence of a mediator and a moderator
  • Methods for estimating propensity scores

Center Applied Research

  • Causality in drug abuse research
  • Causality in HIV/risky sexual behavior research
  • Causality in smoking research