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Published on: September 19, 2018
A caveat concerning the application of the jack-knife to designed data
1Chemometry Consultancy, Rubensstraat 7, 6717 VD Ede, The Netherlands. nmf@chemometry.com
Abstract:
The jack-knife is a resampling method that is increasingly used for assessing the uncertainty in regression coefficient estimates, even when the predictor variables (X) are designed. Application of the jack-knife to designed data, however, violates a basic assumption underlying all resampling methods, namely that the resampled units should constitute a random sample from some distribution; the idea is to 'resample the sample.' This paper advances the view that the jack-knife should not be applied to estimate the uncertainty in regression coefficient estimates obtained from designed data, since a sound alternative is available. A literature data set is re-analyzed to lend support to this view.
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