ArticleJournal of the Royal Statistical Society. Series B, Statistical methodology2024
Identification and estimation of causal peer effects using double negative controls for unmeasured network confounding.
Article in Journal of the Royal Statistical Society. Series B, Statistical methodology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- Revisiting the effects of maternal education on adolescents' academic performance: Doubly robust estimation in a network-based observational study.Journal of the Royal Statistical Society. Series C, Applied statistics · 2024Article
- Double Negative Control Inference in Test-Negative Design Studies of Vaccine Effectiveness.Journal of the American Statistical Association · 2024Article
- INTRODUCING PROXIMAL CAUSAL INFERENCE FOR EPIDEMIOLOGISTS.American journal of epidemiology · 2023Article
- Double Negative Control Inference in Test-Negative Design Studies of Vaccine Effectiveness.ArXiv · 2023Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Identification and estimation of causal peer effects are challenging in observational studies for two reasons. The first is the identification challenge due to unmeasured network confounding, for example, homophily bias and contextual confounding. The second is network dependence of observations. We establish a framework that leverages a pair of negative control outcome and exposure variables (double negative controls) to non-parametrically identify causal peer effects in the presence of unmeasured network confounding. We then propose a generalised method of moments estimator and establish its consistency and asymptotic normality under an assumption about
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.