A Critical Perspective on the Analysis of Event-Related Potentials based on Averages – Juan Carlos Oliver Rodríguez
Repeated measures Anova or Manova are frequently used for analyzing event-related brain potentials. They are typically performed on averaged repeated stimulus trials as a way of increasing the reliability of the electroencephalogram signal. Averaging, however, leads to information loss concerning the covariance matrix of random individual differences of participant treatment and time effects, which could be of substantive interest. Lack of adequate specification of the covariance matrix has also been shown to lead to inferential biases. The objective of the present study is to compare performance of this traditional approach with that of multilevel models which allow for an explicit modelling of these random effects using single trial measures. The number of stimulus repetitions (10, 20 and 30), participants (10 to 100) as well as the data generating model (random intercepts vs random coefficients) were manipulated in a simulation of a facial perception experiment. Empirical power, Type I Error, and effect sizes were obtained as performance measures. Type I error biases were observed in the conditions with averaged trials and random coefficients. Small sample inference considerations will be discussed along with more general implications for the analysis of event-related brain potentials.
Juan Carlos Oliver Rodríguez
Universitat Jaume I