Table 9. Generalized additive model for the response latencies in experiment 1, using discrimination-based predictors.

A. parametric coefficients	Estimate	Std. Error	t-value	p-value
Intercept	-1.5789	0.0278	-56.7847	0.0000
Experiment = 1a	-0.0546	0.0278	-1.9627	0.0497
PrimeType = decomposable	-0.0178	0.0094	-1.8919	0.0586
B. smooth terms	edf	Ref.df	F-value	p-value
tensor product smooth G2L prior by G2L a-diversity by Spelling	11.1763	13.6993	2.2615	0.0054
tensor product smooth L2L prior by L2L l-diversity	4.6038	4.6664	3.4792	0.0047
by-Target random intercepts	24.5204	30.0000	12.2987	0.0000
by-Prime random intercepts	28.2487	103.0000	0.4863	0.0010
by-Previous-Target random intercepts	43.4725	139.0000	0.4600	0.0002
by-Participant factor smooths for Trial	392.9230	1527.0000	2.0703	0.0000

AIC = 1237.009; fREML = 877.48; R-sq. = 0.494.