Comparison of Two Bayesian Methods in Evaluation of the Absence of the Gold Standard Diagnostic Tests

Table 5

The posterior estimation of four models using the TB data under conditional independence situation.

Situation	Method	Model	Knot	Mean	SD	Median	95% Bayesian CI
							(P2.5-P97.5)
No prior constraints	Bayesian probabilistic constraint model	NP		0.660	0.243	0.762	0.503-0.841
				0.418	0.251	0.426	0.203-0.584
				0.511	0.251	0.568	0.302-0.688
				0.569	0.249	0.631	0.377-0.759
				0.512	0.194	0.515	0.361-0.667
	Conditional; Covariance; Bayesian model	NC		0.618	0.250	0.631	0.071-0.974
				0.377	0.250	0.295	0.025-0.929
				0.468	0.255	0.435	0.036-0.947
				0.526	0.253	0.480	0.055-0.962
				0.498	0.194	0.497	0.148-0.850
Prior constraints	Bayesian probabilistic constraint model	PP		0.738	0.036	0.739	0.714-0.762
				0.454	0.051	0.453	0.419-0.487
				0.585	0.031	0.585	0.563-0.606
				0.525	0.028	0.525	0.506-0.544
				0.534	0.042	0.534	0.506-0.562
	Conditional; Covariance; Bayesian model	PC		0.898	0.039	0.910	0.814-0.963
				0.765	0.125	0.775	0.515-0.968
				0.594	0.048	0.586	0.523-0.712
				0.679	0.048	0.676	0.592-0.780
				0.636	0.086	0.650	0.435-0.773

: sensitivity of T-SPOT; : specificity of T-SPOT; : sensitivity of KD38; : specificity of KD38;: prevalence within the patients in the study; SD: standard deviation; CI: confidence interval.