Table 2.

Parameter Estimates From Models of Vigilance for Retreat 1

Model and parameter	Estimate	Test statistic	BIC
Pretraining			–902
Fixed effects
β0 (intercept)	0.972	t = 212**
β1 (slope)	–0.006	t = 3.94***
Random effects
σ02 (intercept)	0.001	z = 4.06***
σe2 (residual variance)	0.001	z = 9.41***
Midtraining			–759
Fixed effects
β0 (intercept)	0.939	t = 142***
β1 (slope)	–0.012	t = 5.37***
Random effects
σ02 (intercept)	0.001	z = 4.39***
σe2 (residual variance)	0.001	z = 9.41***
Posttraining			–765
Fixed effects
β0 (intercept)	0.936	t = 149**
β1 (slope)	–0.013	t = 6.12***
Random effects
σ02 (intercept)	0.001	z = 4.20***
σe2 (residual variance)	0.001	z = 9.41***

Note: Full maximum likelihood estimates are reported for the best-fitting models of change in perceptual sensitivity during sustained performance (n = 59 at all assessments). Slope estimates refer to the amount of decrease in sensitivity per block (four blocks). BIC is the Bayesian information criterion; smaller (more negative) values indicate a better model fit. At each assessment, slope was centered to the first block of the sustained-attention task (Block 1 = 0). In all cases, the simpler models (shown here) were better fits than models that included group and interaction effects (not shown; BIC = –898 for pretraining, –751 for midtraining, and –759 for posttraining).

^**p < .01.

^***p < .001.