The resampling method of statistical analysis.
Some non-statisticians occasionally use improper statistical methodology due to a lack of appreciation for the model assumptions that underlie a particular technique. The resampling method is a recent attempt to solve statistical problems with a minimum of assumptions. In essence, resampling involves an intuitive approach to inferential statistics that obviates the need for the mathematically derived sampling distribution. The resampling approach takes advantage of readily accessible high-speed computers to do a computationally intensive Monte Carlo experiment on the available data. The resampling approach liberates the user from imposing assumptions that are sometimes dubious. It also directs one away from a black-box attitude toward statistical analysis and instead forces the user to consider the purpose of the inferential process. A particularly user-friendly implementation of resampling methods that addresses some of the problems faced by non-statisticians is found in a simple, yet powerful, computer program called "Resampling Stats," version 3.13.
Pollack
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Hillside Hospital, Long Island Jewish Medical Center, Glen Oaks, NY 11004.
Bruce
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Borenstein
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Lieberman
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D000328:Adult; D005260:Female; D006801:Humans; D008297:Male; D009010:Monte Carlo Method; D012107:Research Design; D012984:Software; D013223:Statistics as Topic