ArticleAmerican journal of public health2018
Evaluating Public Health Interventions: 8. Causal Inference for Time-Invariant Interventions.
Article in American journal of public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 9 citations in OpenAlex.
- Analysis of patient activation and its influencing factors among Chinese rural older adults with chronic multimorbidity.Frontiers in public health · 2026Observational
- Navigating grey areas in HIV and mental health implementation science.Journal of the International AIDS Society · 2024Article
- Using Randomized Controlled Trials to Estimate the Effect of Community Interventions for Childhood Asthma.Preventing chronic disease · 2023Article
- ANALYSIS OF "LEARN-AS-YOU-GO" (LAGO) STUDIES.Annals of statistics · 2021Article
- Guarding Against Seven Common Threats to the Credible Estimation of COVID-19 Policy Effects.American journal of public health · 2020Article
- Article
- Optimizing the development and evaluation of complex interventions: lessons learned from the BetterBirth Program and associated trial.Implementation science communications · 2020Article
- Antipseudomonal monotherapy or combination therapy for older adults with community-onset pneumonia and multidrug-resistant risk factors: a retrospective cohort study.American journal of infection control · 2019Article
- Effect Modification and Collapsibility in Evaluations of Public Health Interventions.American journal of public health · 2019Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
We provide an overview of classical and newer methods for the control of confounding of time-invariant interventions to permit causal inference in public health evaluations. We estimated the causal effect of gender on all-cause mortality in a large HIV care and treatment program supported by the President's Emergency Program for AIDS Relief in Dar es Salaam, Tanzania, between 2004 and 2012. We compared results from multivariable modeling, three propensity score methods, inverse-probability weighting, doubly robust methods, and targeted maximum likelihood estimation. Considerable confounding was evident, and, as expected by theory, all methods considered gave the same result, a statistically significant approximately 20% increased mortality rate in men. In general, there is no clear advantage of any of these methods for causal inference over classical multivariable modeling, from the point of view of either bias reduction or efficiency. Rather, given sufficient data to adequately fit the multivariable model to the data, multivariable modeling will yield causal estimates with the greatest statistical efficiency. All methods can adjust only for well-measured confounders-if there are unmeasured or poorly measured confounders, none of these methods will yield causal estimates.
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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.