This article concentrates on one of the newer techniques, namely, resampling, and attempts to address the above issues. First, concepts of different types of resampling will be introduced with simple examples. Next, software applications for resampling are illustrated. Contrary to popular beliefs, many resampling tools are available in standard statistical applications such as SAS and SyStat. Resampling can also be performed in spreadsheet programs such as Excel. Last but not least, arguments for and against resampling are discussed. I propose that there should be more than one way to construe probabilistic inferences and that counterfactual reasoning is a viable means to justify use of resampling as an inferential tool. Accessed 125,653 times on https://pareonline.net from September 29, 2003 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right.
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This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Yu, Chong Ho
"Resampling methods: Concepts, Applications, and Justification,"
Practical Assessment, Research, and Evaluation: Vol. 8
, Article 19.
Available at: https://scholarworks.umass.edu/pare/vol8/iss1/19