Table 2:

Simulation results from 10,000 MC runs when the true model is an upper hinge linear model. Mean estimate, %bias, coverage, and MC SD of the parameter estimate are given for both the segmented and upper hinge models. Additionally, the ratios of the MC standard deviation of the parameter estimates from the two models fit are given.

		Segmented Model			Upper Hinge Model
	n	Est(%Bias)	Coverage	MC SD	Est(%Bias)	Coverage	MC SD	SD Ratio
${\mathit{\beta }}_z$
	50	1.00 (0)	0.945	0.07	1.00 (0)	0.941	0.06	1.02
	100	1.00 (0)	0.946	0.04	1.00 (0)	0.946	0.04	1.01
	500	1.00 (0)	0.944	0.02	1.00 (0)	0.945	0.02	1.00
${\beta }_{(x-e)-}$
	50	1.12 (12)	0.985	0.54	1.02 (2)	0.959	0.22	2.47
	100	1.04 (4)	0.977	0.19	1.01 (1)	0.961	0.13	1.44
	500	1.00 (0)	0.962	0.06	1.00 (0)	0.956	0.05	1.03
$e$
	50	2.97	0.968	0.84	3.01	0.950	0.50	1.69
	100	3.00	0.968	0.50	3.00	0.961	0.31	1.62
	500	3.00	0.962	0.19	3.00	0.956	0.13	1.45