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Beyond curve fitting? Comment on Liu, Mayer-Kress, and Newell (2003)

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posted on 2025-05-11, 10:17 authored by A. Heathcote, Scott Brown
Y.-T. Liu, G. Mayer-Kress. and K. M. Newell (2003) fit learning curves to movement time data and suggested 2 new methods for analyzing learning. They claimed that the methods go "beyond curve fitting.' However, in neither their curve fitting nor their new methods is measurement noise accounted for, and therefore they produce inefficient and biased results. Using the data of Liu et al., in which variance caused by learning is small relative to the level of noise for most participants, the present authors demonstrate those problems and provide better alternatives that are more noise tolerant, more powerful, and go beyond curve fitting without displaying the extreme bias produced by the methods of Liu et al.

History

Journal title

Journal of Motor Behavior

Volume

36

Issue

2

Pagination

225-232

Publisher

Heldref Publications

Language

  • en, English

College/Research Centre

Faculty of Science and Information Technology

Rights statement

This is an electronic version of an article published in The Journal of Motor Behavior Vol. 36, Issue 2, p. 225-232. The Journal of Motor Behavior is available online at: http://www.tandfonline.com/openurl?genre=article&issn=0022-2895&volume=36&issue=2&spage=225

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