title: Functional principal components analysis of workload capacity functions.
abstract: 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.
authors.affiliation: Psychological and Brain Sciences, Indiana University, 1101 E 10th St, Bloomington, IN, 47405, USA, devburns@indiana.edu.
authors.forename: Devin M
authors.initials: DM
authors.lastname: Burns
authors.forename: Joseph W
authors.initials: JW
authors.lastname: Houpt
authors.forename: James T
authors.initials: JT
authors.lastname: Townsend
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Endres
mesh_terms: D006801:Humans; D008960:Models, Psychological; D015233:Models, Statistical; D025341:Principal Component Analysis; D011930:Reaction Time; D014938:Work Capacity Evaluation; D016526:Workload / Q000523:psychology*