Evidence map›Paper›PMID 42453562›Full record

ArticleJournal of the Royal Statistical Society. Series A, (Statistics in Society)2026

COADVISE: covariate adjustment with variable selection in randomized controlled trials.

Yi Liu, Ke Zhu, Larry Han, Shu Yang

Abstract read
In one paragraph

Article in Journal of the Royal Statistical Society. Series A, (Statistics in Society), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Yi LiuDepartment of Statistics, North Carolina State University, Raleigh, NC 27695, USA.
Ke ZhuDepartment of Statistics, North Carolina State University, Raleigh, NC 27695, USA.ORCID https://orcid.org/0000-0001-8778-0086
Larry HanDepartment of Public Health and Health Sciences, Northeastern University, Boston, MA 02115, USA.
Shu YangDepartment of Statistics, North Carolina State University, Raleigh, NC 27695, USA.ORCID https://orcid.org/0000-0001-7703-707X

Funding

Integrated Biostatistical Training for CVD ResearchT32HL079896 · NHLBI · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI Sean M O'Brien, Ana-Maria Staicu · 2006 to 2026
$4.1M
FDA HHS U01 FD007934NHLBI NIH HHS T32 HL079896
6 · The paper itself

Abstract

Adjusting for covariates in randomized controlled trials can enhance the credibility and efficiency of treatment effect estimation. However, handling numerous covariates and their complex (nonlinear) transformations poses a challenge. Motivated by the case study of the Best Apnea Interventions for Research (BestAIR) trial data from the National Sleep Research Resource (NSRR), where the number of covariates (

Indexed as

complete randomizationcovariate balanceefficiency gainhigh-dimensional datamodel misspecification

Identifiers

PMID42453562
PMCPMC13366223

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.