Table 6. Full results from the ANOVAs for the word-aid recognition test.

Hits	Type of Script	F(1, 110) = 21.489, p < .001, ηp2 = .163 ***
	Aid	F(1, 110) = 1.729, p = .191, ηp2 = .015
	Number of Scripts	F(1, 110) = 0.034, p = .855, ηp2 = .000
	Type of Script*Aid	F(1, 110) = 0.039, p = .843, ηp2 = .000
	Type of Script*Number of Scripts	F(1, 110) = 1.050, p = .308, ηp2 = .009
	Aid*Number of Scripts	F(1, 110) = 2.534, p = .114, ηp2 = .023
	Type of Script*Aid*Number of Scripts	F(1, 110) = 0.531, p = .468, ηp2 = .005
False alarms	Type of Script	F(1, 110) = 13.256, p < .001, ηp2 = .108 ***
	Aid	F(1, 110) = 13.446, p < .001, ηp2 = .109 ***
	Number of Scripts	F(1, 110) = 1.782, p = .185, ηp2 = .016
	Type of Script*Aid	F(1, 110) = 1.027, p = .313, ηp2 = .009
	Type of Script*Number of Scripts	F(1, 110) = 0.564, p = .454, ηp2 = .005
	Aid*Number of Scripts	F(1, 110) = 0.229, p = .633, ηp2 = .002
	Type of Script*Aid*Number of Scripts	F(1, 110) = 2.079, p = .153, ηp2 = .018
A′	Type of Script	F(1, 110) = 1.601, p = .208, ηp2 = .014
	Aid	F(1, 110) = 6.377, p = .013, ηp2 = .055 *
	Number of Scripts	F(1, 110) = 1.087, p = .300, ηp2 = .010
	Type of Script*Aid	F(1, 110) = 0.435, p = .511, ηp2 = .004
	Type of Script*Number of Scripts	F(1, 110) = 1.810, p = .181, ηp2 = .016
	Aid*Number of Scripts	F(1, 110) = 1.185, p = .279, ηp2 = .011
	Type of Script*Aid*Number of Scripts	F(1, 110) = 1.901, p = .171, ηp2 = .017
B′′D	Type of Script	F(1, 110) = 27.601, p < .001, ηp2 = .201 ***
	Aid	F(1, 110) = 13.243, p < .001, ηp2 = .107 ***
	Number of Scripts	F(1, 110) = 1.134, p = .289, ηp2 = .010
	Type of Script*Aid	F(1, 110) = 3.080, p = .082, ηp2 = .027
	Type of Script*Number of Scripts	F(1, 110) = 0.399, p = .529, ηp2 = .004
	Aid*Number of Scripts	F(1, 110) = 0.030, p = .863, ηp2 = .027
	Type of Script*Aid*Number of Scripts	F(1, 110) = 1.081, p = .301, ηp2 = .010

Note:

* p < .05;

** p < .01;

*** p < .001