Table 5.

Linear models for 36 month language outcomes.

A) Model 1: Predicting continuous language outcome (CELF-P2 score)
	Estimate	Std. Error	t-value	p-value
(Intercept)	140.4	21.7	6.48	<.0001
Vocabulary Percentile – 18 months	−0.045	0.115	−0.394	0.695
Vocabulary Percentile – 24 months	0.023	0.097	0.243	0.809
GCC – 18 months	17.358	8.523	2.037	0.048
GCC – 24 months	−94.815	37.841	−2.506	0.016
LogGaze – 18 months – SemRel	3.510	3.665	0.958	0.343
LogGaze – 18 months - SemUnrel	7.371	4.332	1.702	0.096
LogGaze – 24 months - SemRel	3.245	4.031	0.805	0.425
LogGaze – 18 months – SemRel	1.348	4.827	0.279	0.781
B) Model 2: Predicting categorical language delay outcome (CELF-P2 < 85 SS)
	Estimate	Std. Error	t-value	p-value
(Intercept)	9.789	6.686	1.464	0.143
Vocabulary Percentile – 18 months	−0.041	0.048	−0.855	0.393
Vocabulary Percentile – 24 months	0.023	0.038	0.609	0.543
GCC – 18 months	5.915	2.869	2.061	0.039
GCC – 24 months	−18.345	11.504	−1.595	0.111
LogGaze – 18 months – SemRel	0.695	1.539	0.452	0.652
LogGaze – 18 months - SemUnrel	3.767	1.850	2.036	0.042
Log Gaze – 24 months - SemRel	1.267	1.346	0.941	0.347
Log Gaze – 24 months - SemUnrel	−0.783	1.729	−0.453	0.651

Significant effects are highlighted in bold.