Table 2.

mvprobit and bvpmvp(…) Comparison: $\widehat{\mathbf{B}}\text{and}\widehat{{\mathbf{B}}_{\mathbf{A}}}$ Point Estimates, One Example (N=10,000, M=4, K=5; Estimated Standard Errors in Parentheses)

Outcome	Covariate	Mvprobit (draws=20)	bvpmvp(…)
y1	x1	0.3265 (.0448)	.3279 (.0446)
	x2	−0.3301 (.0447)	−.3314 (.0447)
	x3	0.3184 (.0447)	.3198 (.0449)
	x4	−0.3902 (.0448)	−.3916 (.0447)
	Constant	0.3901 (.0466)	.3909 (.0464)
y2	x1	−0.4487 (.0456)	−.4487 (.0455)
	x2	0.5624 (.0458)	.5620 (.0456)
	x3	−0.3998 (.0457)	−.3977 (.0457)
	x4	0.4000 (.0456)	.3961 (.0457)
	Constant	−0.5086 (.0474)	−.5079 (.0474)
y3	x1	0.3102 (.0445)	.3151 (.0446)
	x2	0.3846 (.0445)	.3875 (.0449)
	x3	−0.3188 (.0446)	−.3206 (.0447)
	x4	−0.3462 (.0446)	−.3496 (.0447)
	Constant	0.3230 (.0463)	.3210 (.0463)
y4	x1	0.4567 (.0455)	.4573 (.0457)
	x2	−0.4438 (.0455)	−.4408 (.0457)
	x3	−0.4489 (.0456)	−.4516 (.0457)
	x4	0.4555 (.0456)	.4499 (.0453)
	Constant	−0.4552 (.0472)	−.4524 (.0472)