Evidence map›Paper›PMID 21611165›Full record

ArticlePloS one2011

Evaluation of jackknife and bootstrap for defining confidence intervals for pairwise agreement measures.

Ana Severiano, João A Carriço, D Ashley Robinson, Mário Ramirez, Francisco R Pinto

Abstract read
In one paragraph

Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

29 citing papers in PubMed.

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  17. TGF-β-mediated enhancement of TScience signaling · 2018
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  18. Prevalence of ThermophilicFrontiers in microbiology · 2018
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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

5 authors.

Ana SeverianoInstituto de Microbiologia, Instituto de Medicina Molecular, Faculdade de Medicina de Lisboa, Lisboa, Portugal.
João A Carriço
D Ashley Robinson
Mário Ramirez
Francisco R Pinto

Funding

Population Genomics of StaphylococciR01GM080602 · NIGMS · UNIVERSITY OF MISSISSIPPI MED CTR · PI ROBINSON, DAVID ASHLEY · 2007 to 2016
$1.8M
NIGMS NIH HHS GM080602NIGMS NIH HHS R01 GM080602
6 · The paper itself

Abstract

Several research fields frequently deal with the analysis of diverse classification results of the same entities. This should imply an objective detection of overlaps and divergences between the formed clusters. The congruence between classifications can be quantified by clustering agreement measures, including pairwise agreement measures. Several measures have been proposed and the importance of obtaining confidence intervals for the point estimate in the comparison of these measures has been highlighted. A broad range of methods can be used for the estimation of confidence intervals. However, evidence is lacking about what are the appropriate methods for the calculation of confidence intervals for most clustering agreement measures. Here we evaluate the resampling techniques of bootstrap and jackknife for the calculation of the confidence intervals for clustering agreement measures. Contrary to what has been shown for some statistics, simulations showed that the jackknife performs better than the bootstrap at accurately estimating confidence intervals for pairwise agreement measures, especially when the agreement between partitions is low. The coverage of the jackknife confidence interval is robust to changes in cluster number and cluster size distribution.

Indexed as

Confidence IntervalsModels, Statistical

Identifiers

PMID21611165
PMCPMC3097183

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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.