Table 3.

Simple linear regression equations for predicting ECAS-B and ECAS-C performance.

	R2	SEE	C	β(ECAS-A)	X - ^X
Predicting ECAS-B from ECAS-A
ALS Specific	0.398	5.29	34.18	0.613	±8.70
ALS Non-Specific	0.297	2.25	15.31	0.490	±3.70
ECAS Total	0.448	6.23	41.62	0.648	±10.24
	R2	SEE	C	β(ECAS-B)	X - ^X
Predicting ECAS-C from ECAS-B
ALS Specific	0.700	5.30	34.18	0.938	±8.72
ALS Non-Specific	0.597	2.00	11.60	0.628	±3.29
ECAS Total	0.741	6.12	14.78	0.872	±10.07

R² is the multiple R². SEE is the residual standard error, C is the intercept, β is the beta coefficient associated with the subscript ECAS, X - ^X is the residual (i.e. the difference between the model predicted score and the observed score). The X - ^X column indicates the number of points difference required between observed and estimated score to determine reliable difference – this is calculated as 1.645*(SEE).