TABLE 8.

Does comprehension of center-embedded clauses interact with bilingualism for cognitive function? glm() regression with Poisson error were used to model cognitive parameters.

	Dependent variable:
	TEA-1	TEA-2	TEA-3	Backward digit span
	(1)	(2)	(3)	(4)
(Intcpt)/Monolingual	1.866	1.881	1.621	1.705
	t = 20.389	t = 20.545	t = 15.451	t = 17.105
	p = 0.000	p = 0.000	p = 0.000	p = 0.000
Bilingual	0.062	0.215	0.241	0.093
	t = 0.507	t = 1.815	t = 1.772	t = 0.700
	p = 0.612	p = 0.070	p = 0.077	p = 0.485
Center-Embedded	−0.025	−0.099	−0.152	−0.069
	t = −0.235	t = −0.947	t = −1.299	t = −0.605
	p = 0.815	p = 0.344	p = 0.194	p = 0.546
Bilingual:	0.011	0.182	0.362	0.155
Center-Embedded	t = 0.088	t = 1.468	t = 2.593	t = 1.122
(Interaction)	p = 0.930	p = 0.143	p = 0.010	p = 0.262
Observations	48	48	48	48
Log Likelihood	−91.369	−107.938	−127.327	−92.858
Akaike Inf. Crit.	190.738	223.875	262.654	193.716

Model 1: TEA-1 ∼ Monoling/Biling × Center-Embedded, Poisson error. Model 2: TEA-2 ∼ Monoling/Biling × Center-Embedded, Poisson error. Model 3: TEA-3 ∼ Monoling/Biling × Center-Embedded, Poisson error. Model 4: Backward digit span ∼ Monoling/Biling × Center-Embedded, Poisson error.