Table 5.

Study 2 Monte Carlo slopes-as-outcomes multilevel models and “Huber–White” OLS results of parameter estimates for Y${}_2$, 5000 replications

Population parameter				RML MLM		FIML MLM		“Huber–White” OLS
Labels	Level	Class	Value	Mean	SD	Mean	SD	Mean	SD
${\mathit{\beta }}_0$ for constant (=${\mathit{\gamma }}_{00})$	1	E	15.00	15.000	.013	15.000	.013	15.054	.347
Standard error for ${\mathit{\beta }}_0$				.013	.001	.013	.001	.267	.111
${\mathit{\beta }}_{1_j}$ for X${}_1$(=${\mathit{\gamma }}_{01})$	2	C	.20	.171	.388	.143	.380	.079	.426
Standard error for ${\mathit{\beta }}_1$				.417	.111	.421	.104	.382	.126
${\mathit{\gamma }}_{11}$ for Z${}_1$	2	A	.30	.318	.354	.267	.348	.281	.399
Standard error for ${\mathit{\gamma }}_{11}$				.418	.163	.428	.157	.314	.157
${\mathit{\beta }}_2$ for X${}_2$(=${\mathit{\gamma }}_{02})$	1	F	.60	.600	.007	.600	.007	.585	.146
Standard error for ${\mathit{\beta }}_2$				.007	.001	.013	.001	.110	.048
${\mathit{\beta }}_{\mathrm{Minority}}$	1	F	-.05	-.001	.027	-.049	.027	-.096	.750
Standard error for ${\mathit{\beta }}_{\mathrm{Minority}}$				.027	.003	.027	.002	.547	.238