Evidence map›Paper›PMID 43024216›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2027

Guide to Extending Findings from Selected Samples Using Inverse Odds of Selection Weights.

Eleanor Hayes-Larson

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2027. 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

1 author.

Eleanor Hayes-LarsonLeonard Davis School of Gerontology, University of Southern California, 3715 McClintock Ave., Los Angeles, CA, 90089, USA. hayeslar@usc.edu.ORCID http://orcid.org/0000-0001-8299-2389

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

When study samples, such as randomized controlled trial participants or individuals in biomarker studies, come from highly selected groups, results may not generalize to broader populations. Statistical methods called transportability methods enable extension of findings from such samples to specified target populations under certain assumptions. Here, we describe the implementation of one transportability method, inverse odds of selection weighting, to extend findings from selected trial samples. We discuss assumptions and data requirements, including harmonization and concatenation of trial and target datasets, and describe estimation, evaluation, and application of inverse odds of selection weights. Throughout, we highlight practical considerations and commonly encountered challenges.

Indexed as

BiomarkersHumansModels, StatisticalResearch DesignSelection BiasBiomarkersExternal validityGeneralizabilityInverse odds of selection weightsSelection biasTransportability

Identifiers

PMID43024216

What OpenQuestion holds

Textmetadata
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.