Recap: An Introduction to Quasi-Experimental Causal Inference Methods
Thank you to all who joined CAFE University’s “An Introduction to Quasi-Experimental Causal Inference Methods” webinar with Rachel Nethery, Associate Professor of Biostatistics at Harvard T.H. Chan School of Public Health and CAFE’s Capacity Building Team’s Co-Lead. During the webinar, Dr. Nethery introduced several key quasi-experimental approaches used to strengthen causal inference in environmental and public health research. If you missed it, or would like to review the key points, here’s a recap:
Why Quasi-Experimental Methods Matter
Estimating the health impacts of extreme weather events can be methodologically challenging because researchers cannot randomly assign communities to experience weather events. Traditional observational comparisons can be biased by underlying differences between populations or broader time trends.
Quasi-experimental methods help address these challenges by leveraging differences in exposure that occur unintentionally or unpredictably, allowing researchers to estimate what would likely have happened in affected communities had the event not occurred. These approaches strengthen causal inference and provide more rigorous evidence for public health decision-making.
Difference-in-Differences: Comparing Changes Over Time
Dr. Nethery first discussed difference-in-differences (DID), a widely used approach that compares changes in outcomes over time between exposed and unexposed groups. DID relies on the parallel trends assumption, which states that outcomes in treated and control groups would have followed similar trends in the absence of exposure.
Key points included:
- DID estimates effects by comparing changes before and after an event in exposed areas relative to changes over the same time periods in comparable control areas that were not exposed.
- Multiple pre-event observations can help assess whether the parallel trends assumption is plausible.
- The method can incorporate time-varying covariates but remains sensitive to unmeasured factors that change over time differently in the exposed and unexposed areas.
Dr. Nethery also highlighted potential challenges in extreme weather studies, including anticipation effects, spillover effects, and differences in exposure intensity across locations.
Synthetic Control Methods: Building Better Counterfactuals
The webinar also introduced the synthetic control method (SCM), which is particularly useful when there is only one or a small number of treated or exposed units. SCM creates a weighted combination of control locations that closely reproduces pre-exposure trends in the treated unit and uses this “synthetic” comparison to estimate the counterfactual outcome.
Compared with DID, SCM often relies on less restrictive assumptions and can better accommodate certain forms of time-varying confounding. Researchers assess its validity by examining how closely the synthetic control matches the treated unit before exposure.
Looking Ahead
Dr. Nethery concluded by discussing newer latent factor model approaches that build on both DID and SCM. These methods allow researchers to analyze multiple treated units, accommodate staggered treatment timing, and address more complex real-world settings. Together, these approaches provide powerful tools for strengthening causal evidence on the health impacts of extreme weather and generating findings that can inform public health policy.
NIH Health and Extreme Weather Program
Health and Extreme Weather is Now a Highlighted Topic
Health and Extreme Weather is now designated as a Highlighted Topic across participating NIH Institutes and Centers.
Rather than waiting for a dedicated funding announcement, investigators are highly encouraged to pursue research through existing NIH funding opportunities that align with the goals of the Health and Extreme Weather Program. These opportunities may include parent R01 grants, fellowships, career development awards, and training and education grants.
One focus of the Health and Extreme Weather Highlighted Topic is training development. The NIH has released three Research Education Program (R25) funding announcements (PA-27-034, PA-27-035, PA-27-036) that support research education and training programs incorporating a health and extreme weather focus.Explore all currently active NIH funding opportunities here.
Future Funding Opportunities are in Development
While there are currently no active HEW-specific funding announcements, NIH shared that two major opportunities are currently under development and listed in the NIH Forecast.
These include:
- Health and Extreme Weather (HEW) Research Coordination and Data Center: Will solicit applications for research coordination and data support for the Health and Extreme Weather (HEW) initiative including two closely aligned components: research coordination and data support. The coordinating component will facilitate engagement across the initiative’s grantees and the larger HEW community of practice. The data component will develop resources and infrastructure to facilitate access to and use of HEW-relevant data resources.
- Health and Extreme Weather Solutions-Focused Research Hubs: Will solicit applications that propose translational research hubs with multiple highly integrated components focused on research, capacity building, and community/public health translation for regionally relevant topics related to the health impacts of extreme weather and cumulative exposures, including but not limited to wildfire smoke, extreme heat, flooding, hurricanes, drought, and other climate-related hazards affecting populations at heightened risk across the lifespan.
Investigators interested in these opportunities should monitor the NIH Forecast for future announcements.
Connect with an NIH Program Officer
A key message from NIH speakers was the importance of engaging with program officers early in the grant development process. Whether you are developing a new research project, training award, or educational initiative, program officers can help investigators determine how well their ideas align with NIH priorities and identify the most appropriate funding mechanisms.
CAFE Research Coordinating Center Updates
The second half of the webinar highlighted new and ongoing resources and opportunities available through the CAFE Research Coordinating Center.
Some of the highlighted resources and opportunities included:
- Half-Day Events: CAFE hosts virtual half-day events featuring expert panels, lightning talks, workshops, and networking opportunities focused on topics in health and extreme weather research.
- Mentorship Program: The next CAFE mentorship cohort will support early-career investigators through grant writing mentorship, guest speakers, and small-group discussions. The call for mentees is open until August 21st.
- Research Matchmaking: CAFE continues to connect researchers with potential collaborators, mentors, datasets, and technical expertise across institutions and disciplines.
- Actionable Solutions Grants Program: CAFE provides seed funding to support activities that strengthen health and extreme weather research, including data collection, training, and community engagement efforts. Deadline September 15th
- Public Narrative Workshop: Participants will learn practical storytelling techniques to communicate their research more effectively to policymakers, communities, and the public. Deadline August 28th.
- Data Resources: CAFE highlighted its growing collection of shared resources, including the Harvard Dataverse repository, GitHub tutorials and code, data management support, and the Educational Resource Hub.
To hear the full discussion and learn more about current and future opportunities, the webinar recording is available here.
Stay connected with CAFE through the newsletter and website for updates on upcoming webinars, conferences, funding opportunities, mentorship programs, and new community resources.
