Effect Aliasing in Observational Studies

• 成果类型: Article
• 署名作者: Rosenbaum, Paul R.; Zubizarreta, Jose R.
• 署名单位: University of Pennsylvania; Harvard University; Harvard Medical School; Harvard University
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459; 1537-274X
• DOI: 10.1080/01621459.2025.2537456
• 发表日期: 2026-01-02
• 页码: 624-635
• 关键词: Aliased contrasts; Cardinality matching; Causal Inference; Fractional factorial; Incomplete blocks; sensitivity-analysis; Heterogeneity

摘要

In experimental design, aliasing of effects occurs in fractional factorial experiments, where certain low order factorial effects are indistinguishable from certain high order interactions: low order contrast weights may be orthogonal to one another, while their higher order interactions are aliased and not identified. In observational studies, aliasing occurs when certain combinations of covariates-for example, time period and various eligibility criteria for treatment-perfectly predict the treatment that an individual will receive, so a covariate combination is aliased with a particular treatment. In this situation, when a contrast among several groups is used to estimate a treatment effect, collections of individuals defined by contrast weights may be balanced with respect to summaries of low-order interactions between covariates and treatments, but necessarily not balanced with respect high-order interactions. We develop a theory of aliasing in observational studies, illustrate that theory in an observational study whose aliasing is more robust than conventional difference-in-differences, and develop a new form of matching to construct balanced confounded factorial designs from observational data. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.