Evidence map›Paper›PMID 39069742›Full record

ArticleThe international journal of biostatistics2024

Comments on "sensitivity of estimands in clinical trials with imperfect compliance" by Chen and Heitjan.

Stuart G Baker, Karen S Lindeman

Abstract read
In one paragraph

Article in The international journal of biostatistics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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.

Stuart G BakerNational Cancer Institute, Bethesda, MD, 20892-9789, USA.
Karen S LindemanDepartment of Anesthesiology, Johns Hopkins Medical Institutions, Baltimore, USA.

Funding

Intramural NIH HHS Z99 CA999999
6 · The paper itself

Abstract

Chen and Heitjan (Sensitivity of estimands in clinical trials with imperfect compliance. Int J Biostat. 2023) used linear extrapolation to estimate the population average causal effect (PACE) from the complier average causal effect (CACE) in multiple randomized trials with all-or-none compliance. For extrapolating from CACE to PACE in this setting and in the paired availability design involving different availabilities of treatment among before-and-after studies, we recommend the sensitivity analysis in Baker and Lindeman (J Causal Inference, 2013) because it is not restricted to a linear model, as it involves various random effect and trend models.

Indexed as

Models, StatisticalClinical Trials as TopicData Interpretation, StatisticalHumansRandomized Controlled Trials as Topiccomplier average causal effectlocal average treatment effectnoncompliancepaired availability designprincipal stratification randomized trial

Identifiers

PMID39069742
PMCPMC11661933

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.