Bayesian analysis
We supplemented frequentist analysis with Bayesian analysis, which can
confirm the probably of the null hypothesis being true given the data
(PH0|D) (Dienes, 2014). This allows us to statistically confirm
that ERP amplitudes are similar in two conditions. We used conventional
Bayes factor parameters of 1/3 and 3. For Bayesian t tests, we used the
default Cauchy prior (with r-scale of 0.707). For Bayesian ANOVA, we
report BF include. This involves parameter estimation and is not
completely consistent between re-runs, so we avoid overinterpretation of
borderline values. Bayesian analyses were run in open source JASP
software (JASP Team, 2022).