Functional principal components analysis of workload capacity functions

被引:17
|
作者
Burns, Devin M. [1 ]
Houpt, Joseph W. [2 ]
Townsend, James T. [1 ]
Endres, Michael J. [3 ]
机构
[1] Indiana Univ, Bloomington, IN 47405 USA
[2] Wright State Univ, Dayton, OH 45435 USA
[3] Neurobehav Res Inc, Honolulu, HI 96814 USA
基金
美国国家科学基金会;
关键词
Workload capacity; Race model; Response times; Principal components analysis; Systems factorial technology; PARALLEL;
D O I
10.3758/s13428-013-0333-2
中图分类号
B841 [心理学研究方法];
学科分类号
040201 ;
摘要
Workload capacity, an important concept in many areas of psychology, describes processing efficiency across changes in workload. The capacity coefficient is a function across time that provides a useful measure of this construct. Until now, most analyses of the capacity coefficient have focused on the magnitude of this function, and often only in terms of a qualitative comparison (greater than or less than one). This work explains how a functional extension of principal components analysis can capture the time-extended information of these functional data, using a small number of scalar values chosen to emphasize the variance between participants and conditions. This approach provides many possibilities for a more fine-grained study of differences in workload capacity across tasks and individuals.
引用
收藏
页码:1048 / 1057
页数:10
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