ArticleAmerican journal of public health2016
Evaluating Public Health Interventions: 3. The Two-Stage Design for Confounding Bias Reduction-Having Your Cake and Eating It Two.
Article in American journal of public health, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Effectiveness of provider communication training for increasing human papillomavirus vaccine initiation at a safety-net health system.Preventive medicine reports · 2024Article
- National estimates from the Youth '19 Rangatahi smart survey: A survey calibration approach.PloS one · 2021Article
- From Epidemiologic Knowledge to Improved Health: A Vision for Translational Epidemiology.American journal of epidemiology · 2019Review
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
In public health evaluations, confounding bias in the estimate of the intervention effect will typically threaten the validity of the findings. It is a common misperception that the only way to avoid this bias is to measure detailed, high-quality data on potential confounders for every intervention participant, but this strategy for adjusting for confounding bias is often infeasible. Rather than ignoring confounding altogether, the two-phase design and analysis-in which detailed high-quality confounding data are obtained among a small subsample-can be considered. We describe the two-stage design and analysis approach, and illustrate its use in the evaluation of an intervention conducted in Dar es Salaam, Tanzania, of an enhanced community health worker program to improve antenatal care uptake.
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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.