Table 1. Regression model results.

A, good organization; B, bad organization.

(A)
	Coefficient	Std. error	Z	P>|z|	95% Conf. Interval
Subject loss	−0.7989	0.0226	35.3	0.0001	0.7546	0.8433
Organization gain	0.1449	0.0120	12.04	0.0001	0.1213	0.1684
cTBS	1.3760	0.5994	2.3	0.022	0.2011	2.5509
Gain organizationxcTBS	−0.0086	0.0075	−1.14	0.254	−0.0233	0.0061
constant	0.2288	0.4353	0.53	0.599	−0.6244	1.0820

(B)
	Coefficient	Std. error	Z	P>|z|	95% Conf. Interval
Subject gain	0.7415	0.0220	33.7	0.0001	0.6983	0.7846
Organization gain	−0.2064	0.0133	−15.43	0.0001	−0.2327	−0.1802
cTBS	0.0022	0.7063	0	0.997	−1.3822	1.3866
Gain organizationxcTBS	0.0376	0.0079	4.72	0.0001	0.0220	0.0533
constant	−1.6118	0.5126	−3.14	0.002	−2.6166	−0.6069

Table 1(A):.

Equation 1: logit (prob. accept) = βo + β₁*GS + β₂*GO + α₀*cTBS + α1*cTBS*GO.

Number of obs = 5800; Number of participants = 29; Obs per group: min = 200; max = 200; avg. = 200.

Integration points = 7, Wald chi2(4)=1342.55.

Log Likelihood = −1948.13, Prob > chi2=0.00001.

Estimate: 1.65; Standard error: 0.21; cTBS: group.

Table 1(B):.

Number of obs = 5800; Number of participants = 29; Obs per group: min = 200; max = 200; avg. = 200.

Integration points = 7, Wald chi2(4)=1294.59.

Log Likelihood = −1902.89, Prob > chi2=0.00001.

Estimate: 1.68; Standard error: 0.25; cTBS: group.