ArticleBiometrika2016
On inverse probability-weighted estimators in the presence of interference.
Article in Biometrika, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
32 citing papers in PubMed.
- A review and evaluation of doubly robust approaches for estimating average treatment effects.Behavior research methods · 2026Review
- Physical activity across mid-life and mortality outcomes in Australian women: A target trial emulation using a prospective cohort.PLoS medicine · 2026Article
- Bipartite interference and air pollution transport: estimating health effects of power plant interventions.Biostatistics (Oxford, England) · 2025Article
- Assessing spillover effects: Handling missing outcomes in network-based studies.Statistical methods in medical research · 2025Article
- Design of egocentric network-based studies to estimate causal effects under interference.Statistical methods in medical research · 2025Article
- Article
- 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
- Physical activity across midlife and health-related quality of life in Australian women: A target trial emulation using a longitudinal cohort.PLoS medicine · 2024Article
- Estimating Causal Effects of HIV Prevention Interventions with Interference in Network-based Studies among People Who Inject Drugs.The annals of applied statistics · 2023Article
- Article
- Methods for Assessing Spillover in Network-Based Studies of HIV/AIDS Prevention among People Who Use Drugs.Pathogens (Basel, Switzerland) · 2023Article
- Livestock, pathogens, vectors, and their environment: A causal inference-based approach to estimating the pathway-specific effect of livestock on human African trypanosomiasis risk.PLOS global public health · 2023Article
- Propensity Score in the Face of Interference: Discussion of.Observational studies · 2023Article
- Toward evaluation of disseminated effects of medications for opioid use disorder within provider-based clusters using routinely-collected health data.Statistics in medicine · 2022Article
- The effect of livestock density on Trypanosoma brucei gambiense and T. b. rhodesiense: A causal inference-based approach.PLoS neglected tropical diseases · 2022Article
- Article
- Inverse probability weighted estimators of vaccine effects accommodating partial interference and censoring.Biometrics · 2022Article
- Causal mediation analysis between resistance exercise and reduced risk of cardiovascular disease based on the Aerobics Center Longitudinal Study.Journal of applied statistics · 2022Article
- A Review of Spatial Causal Inference Methods for Environmental and Epidemiological Applications.International statistical review = Revue internationale de statistique · 2021Article
- AVERAGE TREATMENT EFFECTS IN THE PRESENCE OF UNKNOWN INTERFERENCE.Annals of statistics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
We consider inference about the causal effect of a treatment or exposure in the presence of interference, i.e., when one individual's treatment affects the outcome of another individual. In the observational setting where the treatment assignment mechanism is not known, inverse probability-weighted estimators have been proposed when individuals can be partitioned into groups such that there is no interference between individuals in different groups. Unfortunately this assumption, which is sometimes referred to as partial interference, may not hold, and moreover existing weighted estimators may have large variances. In this paper we consider weighted estimators that could be employed when interference is present. We first propose a generalized inverse probability-weighted estimator and two Hájek-type stabilized weighted estimators that allow any form of interference. We derive their asymptotic distributions and propose consistent variance estimators assuming partial interference. Empirical results show that one of the Hájek estimators can have substantially smaller finite-sample variance than the other estimators. The different estimators are illustrated using data on the effects of rotavirus vaccination in Nicaragua.
Indexed as
Identifiers
What OpenQuestion holds
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.