Evidence map›Paper›PMID 40534499›Full record

ArticleStatistical methods in medical research2025

Incorporation of missing indicator with multiple imputation in propensity score analysis with partially observed covariates: A simulation study.

Sevinc Puren Yucel Karakaya, Ilker Unal

Abstract read
In one paragraph

Article in Statistical methods in medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Sevinc Puren Yucel KarakayaDepartment of Biostatistics, School of Medicine, Cukurova University, Turkey.ORCID 0000-0002-5768-3549
Ilker UnalDepartment of Biostatistics, School of Medicine, Cukurova University, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

One of the primary challenges encountered in propensity score (PS) weighting is the presence of observations with missing covariates. In such cases, several potential solutions based on multiple imputation have been proposed. The most prevalent of these is the MI

Indexed as

Propensity ScoreBiasComputer SimulationConfounding Factors, EpidemiologicData Interpretation, StatisticalHumansModels, Statisticalmissing datamissing indicatormultiple imputationPropensity score weightingunmeasured confounding

Identifiers

PMID40534499
PMCPMC12308044

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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.