This study examined the efficiency of different time
series analysis techniques to extract information on the
coupling of spontaneous phasic physiological responses. We
compared four bivariate approaches, cross-spectral,
cross-covariance, cross-covariance with prewhitening, and
dynamic factor analysis, in their ability to yield unbiased
estimates of (a) shared variance, (b) covariance, (c) strength
of relationship, and (d) interchannel time-lag in empirical
and simulated interbeat interval–electrodermal activity
(IBI–EDA) time series. All methods produced similar
estimates of the grand-averaged IBI–EDA dynamics,
but only the measures of covariance produced reliable and
unbiased estimates of the interindividual distribution of
IBI–EDA coupling. We conclude that the extraction of
phasic response patterns during continuous and unrestricted
experimental situations may considerably facilitate
psychophysiological research.