Open AccessMore potential in statistical analyses of event‐related potentials: a mixed regression approach
Author(s) -
Vossen Helen,
Van Breukelen Gerard,
Hermens Hermie,
Van Os Jim,
Lousberg Richel
Publication year - 2011
Publication title -
international journal of methods in psychiatric research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.275
H-Index - 73
eISSN - 1557-0657
pISSN - 1049-8931
DOI - 10.1002/mpr.348
Subject(s) - covariate , mixed model , univariate , analysis of variance , statistics , repeated measures design , regression analysis , habituation , psychology , regression , linear regression , electroencephalography , event related potential , random effects model , mixed design analysis of variance , multilevel model , mathematics , multivariate statistics , meta analysis , medicine , psychiatry , psychotherapist
Despite many developments in the methods of event‐related potentials (ERPs), little attention has gone out to the statistical handling of ERP data. Trials are often averaged, and univariate or repeated measures of analysis of variance (ANOVA) are used to test hypotheses. The aim of this study was to introduce mixed regression to ERP research and to demonstrate advantages associated with this method. Eighty‐five healthy subjects received electrical pain stimuli with simultaneous electroencephalography (EEG) registration. Analyses first showed that results obtained with mixed regression analyses are highly comparable to those using repeated measures of ANOVA. Second, important advantages of the mixed regression technique were demonstrated by allowing the inclusion of persons with missing data, single trial analysis, non‐linear time effects, time × person effects (random slope effects) and a within‐subject covariate. Among others, the results showed a strong trial (habituation) effect, which contraindicates the common procedure of averaging of trials. Furthermore, the regression coefficients for intensity and trial varied significantly between persons, indicating individual differences in the effect of intensity and trial on the ERP amplitude. In conclusion, using mixed regression analysis as a statistical technique in ERP research will advance the science of unravelling mechanisms underlying ERP data. Copyright © 2011 John Wiley & Sons, Ltd.