Progressive smoothing of psychophysiological time series increased the efficiency of detecting response coupling without increasing the probability of Type I error.
Applying moving average smoothers to psychophysiological time series improves the detection of coupled responses without inflating Type I error rates.
Abstract We examined the use of smoothing to enhance the detection of response coupling from the activity of different response systems. Three different types of moving average smoothers were applied to both simulated interbeat interval (IBI) and electrodermal activity (EDA) time series and to empirical IBI, EDA, and facial electromyography time series. The results indicated that progressive smoothing increased the efficiency of the detection of response coupling but did not increase the probability of Type I error. The power of the smoothing methods depended on the response characteristics. The benefits and use of the smoothing methods to extract information from psychophysiological time series are discussed.
Kettunen et al. (Sat,) reported a other. Moving average smoothers was evaluated on Detection of response coupling. Progressive smoothing of psychophysiological time series increased the efficiency of detecting response coupling without increasing the probability of Type I error.