Evidence map›Paper›PMID 32454530›Full record

ArticleBiometrika2020

Consistency for the tree bootstrap in respondent-driven sampling.

A K B Green, T H McCormick, A E Raftery

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biometrika, 2020. 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

3 authors.

A K B GreenScottish Government, Atlantic Quay, 150 Broomielaw, Glasgow G2 8LU, UK.
T H McCormickDepartment of Statistics, University of Washington, Seattle, Washington 98195-4322, USA.
A E RafteryDepartment of Statistics, University of Washington, Seattle, Washington 98195-4322, USA.

Funding

Statistical Methods for Population ProjectionsR01HD070936 · NICHD · UNIVERSITY OF WASHINGTON · PI RAFTERY, ADRIAN E · 2012 to 2021
$3.3M
NICHD NIH HHS R01 HD070936
6 · The paper itself

Abstract

Respondent-driven sampling is an approach for estimating features of populations that are difficult to access using standard survey tools, e.g., the fraction of injection drug users who are HIV positive. Baraff et al. (2016) introduced an approach to estimating uncertainty in population proportion estimates from respondent-driven sampling using the tree bootstrap method. In this paper we establish the consistency of this tree bootstrap approach in the case of [Formula: see text]-trees.

Indexed as

Block bootstrapConsistencyRespondent-driven samplingTree bootstrap

Identifiers

PMID32454530
PMCPMC7228542

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.