Table 3.

Type-I error for testing β_g = 0 at various α levels under correctly specified model scenarios. Four different models were compared: independent Cox (Cox-I), Cox with robust variance estimates (Cox-R), copula with parametric margins (Cop-PM) and coupla with piecewise constant hazards margins (Cop-PW). Number of replication = 100,000, sample size = 500.

		Kendall’s τ = 0.2				Kendall’s τ = 0.6
MAF	Tail (α)	Cox-I	Cox-R	Cop-PM	Cop-PW	Cox-I	Cox-R	Cop-PM	Cop-PW
		True model: Clayton-Weibull
5%	0.05	0.084	0.062	0.052	0.044	0.141	0.063	0.053	0.046
	0.01	0.022	0.016	0.011	0.009	0.053	0.017	0.012	0.009
	0.001	0.0034	0.0029	0.0012	0.0009	0.0129	0.0030	0.0014	0.0010
	0.0001	0.0007	0.0007	0.0001	0.0001	0.0035	0.0007	0.0002	0.0002
40%	0.05	0.086	0.054	0.052	0.045	0.142	0.055	0.053	0.046
	0.01	0.023	0.012	0.011	0.009	0.054	0.012	0.011	0.009
	0.001	0.0040	0.0015	0.0013	0.0008	0.0132	0.0014	0.0012	0.0009
	0.0001	0.0007	0.0002	0.0001	0.0001	0.0033	0.0001	0.0001	0.00004
		True model: Clayton-Gompertz
5%	0.05	0.083	0.061	0.053	0.044	0.138	0.062	0.053	0.044
	0.01	0.022	0.016	0.011	0.008	0.051	0.016	0.011	0.009
	0.001	0.0034	0.0029	0.0012	0.0009	0.0129	0.0030	0.0014	0.0010
	0.0001	0.0006	0.0006	0.0002	0.0001	0.0032	0.0007	0.0002	0.0001
40%	0.05	0.084	0.054	0.052	0.044	0.140	0.054	0.052	0.044
	0.01	0.023	0.012	0.011	0.008	0.053	0.012	0.011	0.008
	0.001	0.0040	0.0015	0.0013	0.0008	0.0132	0.0014	0.0012	0.0009
	0.0001	0.0007	0.0002	0.0001	0.0001	0.0036	0.0001	0.0002	0.0001