Evidence map›Paper›PMID 34018204›Full record

ArticleStatistics in medicine2021

Transporting experimental results with entropy balancing.

Kevin P Josey, Seth A Berkowitz, Debashis Ghosh, Sridharan Raghavan

Abstract read
In one paragraph

Article in Statistics in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed.

  1. Article
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  9. Model-based standardization using multiple imputation.BMC medical research methodology · 2024
    Article
  10. Article
  11. Causal Inference Methods for Combining Randomized Trials and Observational Studies: A Review.Statistical science : a review journal of the Institute of Mathematical Statistics · 2024
    Article
  12. Article
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  14. Observational
  15. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Kevin P JoseyDepartment of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.ORCID 0000-0003-2490-6272
Seth A BerkowitzDivision of General Medicine and Clinical Epidemiology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA.
Debashis GhoshDepartment of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.ORCID 0000-0001-6618-1316
Sridharan RaghavanRocky Mountain Regional VA Medical Center, Aurora, Colorado, USA.ORCID 0000-0003-0643-4873

Funding

University of Colorado Anschutz Medical Campus DRCP30DK116073 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI MARIAN J REWERS · 2020 to 2026
$10.8M
Understanding & Overcoming Food Insecurity in Diabetes PatientsK23DK109200 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BERKOWITZ, SETH A · 2016 to 2020
$973k
Machine Learning and Longitudinal Analyses of Metformin Response Among VeteransIK2CX001907 · VA · VA EASTERN COLORADO HEALTH CARE SYSTEM · PI RAGHAVAN, SRIDHARAN · 2019 to 2023
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CSRD VA IK2 CX001907NIDDK NIH HHS K23 DK109200NIDDK NIH HHS P30 DK116073
6 · The paper itself

Abstract

We show how entropy balancing can be used for transporting experimental treatment effects from a trial population onto a target population. This method is doubly robust in the sense that if either the outcome model or the probability of trial participation is correctly specified, then the estimate of the target population average treatment effect is consistent. Furthermore, we only require the sample moments of the effect modifiers drawn from the target population to consistently estimate the target population average treatment effect. We compared the finite-sample performance of entropy balancing with several alternative methods for transporting treatment effects between populations. Entropy balancing techniques are efficient and robust to violations of model misspecification. We also examine the results of our proposed method in an applied analysis of the Action to Control Cardiovascular Risk in Diabetes Blood Pressure trial transported to a sample of US adults with diabetes taken from the National Health and Nutrition Examination Survey cohort.

Indexed as

Models, StatisticalResearch DesignAdultEntropyHumansNutrition SurveysProbabilitycalibrationcausal inferenceeffect modificationgeneralizability

Identifiers

PMID34018204
PMCPMC8487904

What OpenQuestion holds

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Registered trials

None linked

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.