Table 1.

Evaluating discovery rate of C_τ and $C_{\tau }^{*}$ indices for intermediate disease that can progress or regress. 1000 simulation data sets of 150 subjects were used. 10 candidate predictors are evaluated: 5 correlated and 5 independent of the disease process. Time to progression and first regression are 69% and 34% right-censored, respectively. For C_τ, only disease progression was used. The $C_{\tau }^{*}$ index uses both disease progression and regression events with outcome-specific weights of 1 and 0.75, respectively. Both indices were evaluated at τ = 25. Negative and positive signs for the bias indicates underestimation and overestimation, respectively. ESD is the empirical standard deviation; ASE is the asymptotic standard error; CP is the coverage probability. False discovery rate (FDR) is defined as the number of independent predictors that reject H₀ divided by the number of all predictors that reject H₀, averaged over 1000 simulation runs. The null hypothesis is H₀ : C_τ = 0.5 or H₀ : $C_{\tau }^{*}$= 0.5.

		Cτ	$C_{\tau }^{*}$
True	Estimate	0.841	0.834
Predictor	Bias	0.000	0.000
	ESD	0.026	0.018
	ASE	0.025	0.018
	CP	0.928	0.929
	Reject H0	1	1
Correlated	Estimate	0.549	0.547
Factors	Bias	0.003	0.000
	ESD	0.045	0.030
	ASE	0.043	0.030
	CP	0.940	0.947
	Reject H0	0.230	0.356
Independent	Estimate	0.500	0.500
Factors	Bias	0.000	0.000
	ESD	0.045	0.030
	ASE	0.044	0.030
	Cov	0.940	0.948
	Reject H0	0.060	0.052
FDR		0.199	0.126