. Author manuscript; available in PMC: 2022 Jan 1.

Published in final edited form as: Struct Equ Modeling. 2021 Mar 23;28(4):609–621. doi: 10.1080/10705511.2021.1878895

Table 4.

Monte Carlo Analysis of Bias in the Point Estimates of the Standardized Effect Size (GMA d)

	Parameter =.3464						Parameter =.6928

N	Average GMA d		SD of GMA d		Percent Bias		Average GMA d		SD of GMA d		Percent Bias
	S	I	S	I	S	I	S	I	S	I	S	I
50	.3545	.3611	.4506	.2700	2.34	4.24	.7108	.7173	.4539	.2764	2.60	3.54
100	.3533	.3544	.3095	.1852	1.99	2.31	.7048	.7058	.3117	.1890	1.73	1.88
150	.3504	.3521	.2532	.1500	1.15	1.65	.7003	.7020	.2551	.1533	1.08	1.33
250	.3468	.3503	.1938	.1150	.12	1.13	.6951	.6987	.1952	.1175	.33	.85
500	.3466	.3484	.1373	.0809	.06	.58	.6939	.6956	.1383	.0825	.16	.40

Mdn	.3504	.3521	.2532	.1500	1.15	1.65	.7003	.7020	.2551	.1533	1.08	1.33

Note. Average GMA d = mean of GMA ds from 10,000 replications. SD of GMA d = standard deviation of GMA ds across 10,000 replications. S = GMA d from slope difference (b_s), I = GMA d from intercept difference (b_i),