. 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 6.

Power to Detect b_s and b_i and Average Standard Errors of GMD D from b_s and b_i

		Power		Average SE of GMA D
N	Pop GMA D	b_s	b_i	b_s*3	b_i
50	.30	.146	.305	.365	.216
50	.60	.384	.793	.365	.216
100	.30	.219	.508	.260	.154
100	.60	.637	.972	.260	.154
150	.30	.297	.663	.212	.126
150	.60	.802	.998	.212	.126
250	.30	.449	.869	.165	.098
250	.60	.947	1.000	.165	.098
500	.30	.726	.990	.117	.069
500	.60	.999	1.000	.117	.069

Mdn		.543	.920	.212	.126

Note. Power is the proportion of replications in which b_s and b_i were statistically significant. Pop GMA D = Population GMA D, b_s*3 = GMA D, b_i = GMA D. Average SE of GMA D is the Monte Carlo-calculated mean of the Standard Errors of the model-estimated mean differences at end of study--b_s*duration (= b_s*3) when derived from b_s (the slope difference) or b_i (the intercept difference).