Fingerprinting time series: Dynamic patterns in self-report and performance measures uncovered by a graphical non-linear method

Totterdell, Peter, Briner, Rob B., Parkinson, Brian and Reynolds, Shirley (1996) Fingerprinting time series: Dynamic patterns in self-report and performance measures uncovered by a graphical non-linear method. British Journal of Psychology, 87 (1). pp. 43-60. ISSN 0007-1269

Full text not available from this repository. (Request a copy)

Abstract

Two simple non-linear techniques are shown to be useful for understanding the dynamics of affect, symptoms, social interaction experience and cognitive performance. The techniques are justified by arguments derived from chaos theory, and demonstrated using data from an intensive time sampling study in which 30 subjects completed a set of self-ratings and a memory task on a hand-held computer every two hours during waking hours for 14 days. The data were pooled and two types of Poincaré plot were constructed for each variable. The first was a plot of each value against its predecessor, and the second was a plot of each change in value from one interval to the next against the previous change. These plots are particularly suitable for uncovering asymmetric state-dependent changes in control between time points. The plots showed a number of distinctive ‘fingerprints’ for the different variables. Altogether, the results suggest that the plots are a novel and useful method for understanding psychological variables in terms of their dynamic control.

Item Type:	Article
Faculty \ School:	Faculty of Medicine and Health Sciences > Norwich Medical School
UEA Research Groups:	Faculty of Medicine and Health Sciences > Research Groups > Psychological Sciences (former - to 2018)
Depositing User:	EPrints Services
Date Deposited:	25 Nov 2010 11:12
Last Modified:	24 Sep 2024 10:32
URI:	https://ueaeprints.uea.ac.uk/id/eprint/14578
DOI:	10.1111/j.2044-8295.1996.tb02576.x

Actions (login required)

View Item