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

Table 7

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

Situation	Method	Model	Knot	Mean	SD	Median	95% Bayesian CI
							(P25-P75)
No prior constraints	Bayesian probabilistic constraint model	NP		0.626	0.218	0.665	0.516-0.773
				0.369	0.217	0.330	0.222-0.476
				0.490	0.167	0.495	0.391-0.585
				0.508	0.167	0.503	0.414-0.616
				0.498	0.248	0.497	0.305-0.692
	Conditional; Covariance; Bayesian model	NC		0.690	0.183	0.708	0.622-0.807
				0.435	0.226	0.390	0.287-0.568
				0.547	0.197	0.535	0.455-0.657
				0.571	0.213	0.562	0.444-0.722
				0.553	0.254	0.578	0.366-0.755
Prior constraints	Bayesian probabilistic constraint model	PP		0.713	0.036	0.714	0.689-0.738
				0.423	0.051	0.421	0.387-0.456
				0.535	0.025	0.535	0.518-0.552
				0.537	0.022	0.537	0.522-0.552
				0.538	0.042	0.539	0.510-0.567
	Conditional; Covariance; Bayesian model	PC		0.904	0.037	0.907	0.881-0.931
				0.796	0.119	0.814	0.715-0.892
				0.588	0.055	0.580	0.551-0.614
				0.677	0.068	0.677	0.631-0.723
				0.649	0.076	0.662	0.608-0.701

: 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.