Literature DB >> 30252026

The upstrap.

Ciprian M Crainiceanu1, Adina Crainiceanu2.   

Abstract

The bootstrap, introduced in Efron (1979. Bootstrap methods: another look at the jackknife. The Annals of Statistics7, 1-26), is a landmark method for quantifying variability. It uses sampling with replacement with a sample size equal to that of the original data. We propose the upstrap, which samples with replacement either more or fewer samples than the original sample size. We illustrate the upstrap by solving a hard, but common, sample size calculation problem. The data and code used for the analysis in this article are available on GitHub (2018. https://github.com/ccrainic/upstrap). Published by Oxford University Press 2018.

Keywords:  Bootstrap; sample size calculation; sampling

Mesh:

Year:  2020        PMID: 30252026     DOI: 10.1093/biostatistics/kxy054

Source DB:  PubMed          Journal:  Biostatistics        ISSN: 1465-4644            Impact factor:   5.899


  3 in total

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Journal:  J Am Heart Assoc       Date:  2022-04-18       Impact factor: 6.106

2.  Use of the p-values as a size-dependent function to address practical differences when analyzing large datasets.

Authors:  Estibaliz Gómez-de-Mariscal; Vanesa Guerrero; Alexandra Sneider; Hasini Jayatilaka; Jude M Phillip; Denis Wirtz; Arrate Muñoz-Barrutia
Journal:  Sci Rep       Date:  2021-10-22       Impact factor: 4.379

3.  Trial of Early Antiviral Therapies during Non-hospitalized Outpatient Window (TREAT NOW) for COVID-19: a summary of the protocol and analysis plan for a decentralized randomized controlled trial.

Authors:  Alexander M Kaizer; Jessica Wild; Christopher J Lindsell; Todd W Rice; Wesley H Self; Samuel Brown; B Taylor Thompson; Kimberly W Hart; Clay Smith; Michael S Pulia; Nathan I Shapiro; Adit A Ginde
Journal:  Trials       Date:  2022-04-08       Impact factor: 2.279

  3 in total

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