Table 1.

Fit results from the generalized linear mixed-effects modeling. Linear fit results indicated the strong predictive capability of this $d_{\mathrm{ind}}^{\prime }$ ($p<0.05$). AIC, Akaike information criterion; BIC, Bayesian information criterion; and STD, standard deviation.

Output of the generalized mixed effects linear regression model
Model form
$P$$({}^{ijkl}Y=1)=\mathrm{\varphi }(\mu +{}^{ijkl}{d}_{\mathrm{ind}}^{\prime }+R_i)$
A: Fixed effects
Effect	Estimate	Standard error	$t$ statistic	$p$ value	95% CI
Intercept ($\mu$)	0.27914	0.059425	4.6974	$2.65\times {10}^{-6}$	0.16266, 0.39562
In vivo detectability index (${}^{ijkl}{d}_{\mathrm{ind}}^{\prime }$)	0.21229	0.016119	13.17	$1.89\times {10}^{39}$	0.1807, 0.24389
B: Random effects
Effect	$N$ level	Type	STD
Reader ($R_i$)	16	Intercept	0.20537
C: Fit statistics
Parameter	AIC	BIC	Log likelihood	Deviance
Model	69953	69976	$-34973$	69947