Jackknife, Bootstrap and Other Resampling Methods in Regression Analysis

Invited Paper Jackknife, Bootstrap and Other Resampling Methods in Regression Analysis'

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Resampling Methods: Randomization Tests, Jackknife and Bootstrap Estimators

Resampling methods are becoming increasingly popular as statistical tools, as they are (generally) very robust, their simplicity is compelling, and their computational demands are (largely) no longer an issue to their widespread implementation. These methods involve either sampling or scrambling the original data numerous times, and we consider three general approaches here. Randomization tests...

Jackknife and Bootstrap Resampling Methods in Statistical Analysis to Correct for Bias

This result is obvious but also useful because it tells us that the sample mean is an unbiased estimate for the exact mean, in the sense that the average of the sample mean, over many repetitions, is the exact mean. An unbiased estimate will become more and more accurate as the number of data points is increased. However, a biased estimate not continue to improve with increasing N once the erro...

Statistics Notes: Bootstrap resampling methods.

the bmj | BMJ 2015;350:h2622 | doi: 10.1136/bmj.h2622 1Department of Health Sciences, University of York, York YO10 5DD, UK 2Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford OX3 7LD, UK; Correspondence to: J M Bland [email protected] Cite this as: BMJ 2015;350:h2622 doi: 10.1136/bmj.h2622 Statis...

Jackknife Resampling