Evidence map›Paper›PMID 42806920›Full record

ArticlePharmaceutical statistics

On the Conservativeness of Robust Variance Estimators in Propensity Score Weighted Cox Models.

Hiroya Morita, Shunichiro Orihara, Fumitaka Shimizu, Masataka Taguri

Abstract read
In one paragraph

Article in Pharmaceutical statistics. 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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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

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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

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5 · Who and what money

Authors and funding

4 authors.

Hiroya MoritaDepartment of Health Data Science, Tokyo Medical University, Tokyo, Japan.ORCID https://orcid.org/0009-0009-1337-1488
Shunichiro OriharaDepartment of Health Data Science, Tokyo Medical University, Tokyo, Japan.ORCID https://orcid.org/0000-0003-0168-1250
Fumitaka ShimizuDepartment of Urology, Juntendo University Graduate School of Medicine, Tokyo, Japan.ORCID https://orcid.org/0000-0002-4608-7645
Masataka TaguriDepartment of Health Data Science, Tokyo Medical University, Tokyo, Japan.ORCID https://orcid.org/0000-0001-8902-0056

Funding

JSPS KAKENHI JP24K14862
6 · The paper itself

Abstract

In propensity score weighted analysis, robust variance that does not account for weight estimation (hereafter, uncorrected variance) is commonly used. In propensity score weighted Cox models (CoxPSW), the uncorrected variance is known to be conservative when weights for the average treatment effect (ATE) are used, but it remains unclear whether this conservativeness also holds for other weighting schemes. This study evaluated the performance of the uncorrected variance in CoxPSW when weights other than ATE are applied. We conducted an asymptotic comparison between the uncorrected variance and a variance estimator that accounts for weight estimation under non-ATE weights. Their performance was further evaluated through simulation studies and real data analysis. The analytical results, simulations, and real data analysis indicated that the uncorrected variance is not necessarily conservative in CoxPSW when weights other than ATE are used. These findings suggest that variance estimators that account for weight estimation should be used when applying CoxPSW.

Indexed as

Propensity ScoreComputer SimulationData Interpretation, StatisticalHumansProportional Hazards ModelsATOATTCox regression modelsinverse probability weightingrobust variance

Identifiers

PMID42806920
PMCPMC13621226

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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.