Table 2.

Cross-Sectional Results of Multiple Linear Regression Analysis Predicting MMSE in Whole Sample

	t	B(SE)	p	F	df	p	Adj. R2
Overall Model 1				21.66	5,148	0.000	0.40
Age	−0.81	−0.01 (0.02)	0.422
Education	2.30	0.09 (0.04)	0.023
VIQ	2.23	0.03 (0.01)	0.027
Clinical Status	−7.05	−2.55 (0.36)	0.000
PiB	−3.27	−1.70 (0.52)	0.001
Overall Model 2				28.82	5,148	0.000	0.48
Age	−1.72	−0.03 (0.02)	0.088
Education	2.02	0.08 (0.04)	0.045
VIQ	2.24	0.03 (0.01)	0.027
Clinical Status	−4.97	−1.85 (0.37)	0.000
T807	−5.73	−3.47 (0.61)	0.000
Overall Model 3				24.09	6,147	0.000	0.48
Age	−1.61	−0.03 (0.02)	0.109
Education	2.04	0.08 (0.04)	0.044
VIQ	2.29	0.03 (0.01)	0.024
Clinical Status	−4.86	−1.82 (0.38)	0.000
PiB	−0.84	−0.47 (0.56)	0.401
T807	−4.62	−3.20 (0.69)	0.000
Overall Model 4				18.76	6,147	0.000	0.41
Age	−0.71	−0.01(0.02)	0.477
Education	2473	0.10 (0.04)	0.015
VIQ	−1.18	−0.08 (0.07)	0.239
Clinical Status	−6.81	−2.47 (0.36)	0.000
PiB	−1.95	−12.55 (6.44)	0.053
PiB×VIQ	1.69	0.09 (0.05)	0.093
Overall Model 5				26.77	6,147	0.000	0.50
Age	−1.64	−0.03(0.02)	0.103
Education	2.14	0.08 (0.04)	0.034
VIQ	−2.43	−0.15 (0.06)	0.016
Clinical Status	−5.21	−1.89 (0.36)	0.000
T807	−3.58	−20.07 (5.61)	0.000
T807×VIQ	2.97	0.14 (0.05)	0.003