Table 2.

Summary of results from backward multiple linear regression models.

	NEI-VFQ “visual functioning”		NEI-VFQ “mental-health symptoms due to vision problems”		SF-12 MCS		SF-12 PCS
	[Radj 2 = 0.37, F(3,94) = 20.08, p < 0.01]		[Radj 2 = 0.38, F(1,96) = 60.75, p < 0.01]		[Radj 2 = 0.30, F(1,93) = 41.34, p < 0.01]		[Radj 2 = 0.18, F(4,90) = 6.31, p = 0.01]
	ß	p	ß	p	ß	p	ß	p
Detection accuracy in HRP	0.38	<0.01	0.01	0.88	−0.11	0.24	0.16	0.47
Detection accuracy central 5° in HRP	0.15	0.39	−0.01	0.92	−0.12	0.19	−0.04	0.78
Reaction time in HRP	0.04	0.78	0.02	0.84	0.03	0.77	−0.38	0.01
Foveal threshold in static perimetry	0.11	0.26	0.05	0.53	−0.01	0.93	−0.10	0.41
Mean threshold in static perimetry	0.02	0.91	0.07	0.41	−0.14	0.12	−0.43	<0.01
Binocular impairment, both eyes residual vision	−0.34	<0.01	−0.11	0.19	0.09	0.34	0.01	0.90
Binocular impairment, one blind eye	−0.39	<0.01	0.07	0.41	−0.01	0.90	−0.17	0.08
NEI-VFQ visual functioning			0.62	<0.01	0.04	0.71	0.07	0.96
NEI-VFQ mental-health problems					0.55	<0.01	0.37	<0.01

p  < 0.05 in italics. Intercorrelations between visual field parameters in the regression for PCS lead to a negative ß-value for the mean threshold in static perimetry.