Key result
The upstrap, a statistical method that samples with replacement either more or fewer samples than the original sample size, can be used to solve complex sample size calculation problems.
The upstrap is proposed as a novel statistical method extending the bootstrap by sampling with replacement more or fewer samples than the original data size.
May aid complex sample size calculations in cardiovascular studies; leaves open validation before routine adoption.
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).
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Crainiceanu et al. (2018) studied this question. The upstrap vs. The bootstrap was evaluated. The upstrap, a statistical method that samples with replacement either more or fewer samples than the original sample size, can be used to solve complex sample size calculation problems.
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