The use of the terms 'and', 'or' and 'not' for refining database searches of literature, as in systematic reviewing. Named after the English mathematician George Boole (1815-1864).
The bootstrap is a statistical method of estimating the distribution of an estimator or test statistic by 'resampling' the data. The term comes from the old idea that you might be able to lift yourself off the ground by pulling on the straps on the backs of your boots. Suppose you have a sample of 20. You 'bootstrap', or approximate, the population from which the sample came by duplicating the sample many times over in a computer simulation of the population. You then draw lots of samples (each size 20) from this artificial bootstrap population. Bootstrapping is particularly useful when data are skewed and sample sizes are modest. It is frequently used in estimating probability distributions of cost-effectiveness ratios, their confidence intervals and variances.
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