Table 4.

Study 2 Monte Carlo means-as-outcomes multilevel models and “Huber–White” OLS results of parameter estimates for Y${}_1$, 5000 replications

Population parameter				RML MLM		FIML MLM		“Huber–White” LS
Labels	Level	Class	Value	Mean	SD	Mean	SD	Mean	SD
${\mathit{\beta }}_{0j}$ for constant (=${\mathit{\lambda }}_{00})$	2	D	10.00	9.841	.312	9.911	.288	9.915	.313
Standard error for ${\mathit{\beta }}_0$				.318	.084	.303	.080	.271	.091
${\mathit{\lambda }}_{10}$ for Z${}_1$	2	B	.25	.277	.329	.263	.306	.265	.311
Standard error for ${\mathit{\lambda }}_{10}$				.316	.116	.307	.112	.231	.101
${\mathit{\beta }}_1$ for X${}_1$(=${\mathit{\lambda }}_{01})$	1	F	.30	.300	.008	.300	.008	.352	.107
Standard error for ${\mathit{\beta }}_1$				.008	.0004	.008	.0004	.084	.031
${\mathit{\beta }}_2$ for X${}_2$(=${\mathit{\lambda }}_{02})$	1	F	.20	.200	.008	.200	.079	.189	.104
Standard error for ${\mathit{\beta }}_2$				.008	.0004	.008	.0003	.083	.028
${\mathit{\beta }}_{\mathrm{Minority}}$	1	F	-.10	-.0003	.031	-.100	.032	-.113	.397
Standard error for ${\mathit{\beta }}_{\mathrm{Minority}}$				.031	.003	.031	.004	.320	.112