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.
机构:
North China Univ Water Conservancy & Hydroelect P, Coll Math & Informat, Zhengzhou 450000, Peoples R ChinaNorth China Univ Water Conservancy & Hydroelect P, Coll Math & Informat, Zhengzhou 450000, Peoples R China
Wang, Zhiliang
Sun, Yalin
论文数: 0引用数: 0
h-index: 0
机构:
North China Univ Water Conservancy & Hydroelect P, Coll Math & Informat, Zhengzhou 450000, Peoples R ChinaNorth China Univ Water Conservancy & Hydroelect P, Coll Math & Informat, Zhengzhou 450000, Peoples R China
Sun, Yalin
Li, Peng
论文数: 0引用数: 0
h-index: 0
机构:
North China Univ Water Conservancy & Hydroelect P, Coll Math & Informat, Zhengzhou 450000, Peoples R ChinaNorth China Univ Water Conservancy & Hydroelect P, Coll Math & Informat, Zhengzhou 450000, Peoples R China
机构:
Univ Newcastle, Sch Humanities Creat Ind & Social Sci, Newcastle, NSW 2308, AustraliaUniv Newcastle, Sch Humanities Creat Ind & Social Sci, Newcastle, NSW 2308, Australia