Table 5.

Bayes factor analysis of first-pass regressions from the critical region in our replication data of the dependency × interference interaction, in grammatical and ungrammatical conditions. Shown are increasingly informative priors on the parameter representing the interaction term in the model; for example, Normal(0,1) means a normal distribution with mean 0 and standard deviation 1. We consider a range of priors here because of the well-known sensitivity of the Bayes factor to prior specification. The Bayes factor analysis shows the evidence in favor of the interaction term being present in the model; a value smaller than 1 favors the null model, and a value larger than 1 favors the full model including the interaction term. A value of larger than 10 is generally considered to be strong evidence for the effect of interest being present (Jeffreys, 1939/1998).

Grammatical conditions
	Prior on Dep × Int effect	Bayes factor in favor of alternative
1	Normal(0,1)	0.57
2	Normal(0,0.8)	0.71
3	Normal(0,0.6)	0.95
4	Normal(0,0.4)	1.36
5	Normal(0,0.2)	1.94
Ungrammatical conditions
	Prior on Dep × Int effect	Bayes factor in favor of alternative
1	Normal(0,1)	1.54
2	Normal(0,0.8)	1.97
3	Normal(0,0.6)	2.54
4	Normal(0,0.4)	3.54
5	Normal(0,0.2)	5.31