Time on Your Side: Aggregating Data in Difference‐In‐Differences Studies
In many scenarios, time aggregation has little impact on difference-in-differences estimators. However, when estimating dynamic effects, especially in staggered timing settings and unbalanced data, we found a tradeoff between precision and power, with finer aggregations being more powerful but less precise. In addition, estimators that use a single reference time point are more sensitive to noise in data measured at finer time scales.
Authors
- Laura A. Hatfield (ORCID: https://orcid.org/0000-0003-0366-3929)
- Carrie Fry (ORCID: https://orcid.org/0000-0003-0661-847X)
- Summer Rak
Institutions
- RTI International (US)
- Vanderbilt University (US)
- University of Chicago (US)
- National Opinion Research Center (US)
- Vanderbilt Health (US)
Publication Details
- Journal
- Health Services Research
- Published
- 2025-05-27
- DOI
- https://doi.org/10.1111/1475-6773.14636
- Primary Topic
- Advanced Causal Inference Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institutes of Health
- National Institute on Aging
- National Institute on Drug Abuse