Table 7.

Comparison of the goodness-of-fit measures of the two structural equation models for the two datasets

	Dataset 1 (real compensation)			Dataset 2 (regression to the mean)
	Model 1	Model 2	Relative fit	Model 1	Model 2	Relative fit
N = 28
χ2[DF]	1.9 [2]	6.25 [3]	4.05 [1]	1.9 [2]	3 [3]	0.89 [1]
p(χ2)	.39	.1	.044 *	.39	.39	.34
RMSEA[95%CI]	.057 [.0004,.338]	.167 [.034,.4]	—	.057 [.0003,.338]	.057 [.0004,.296]	—
CFI	.985	.908	—	.99	.986	—
AIC	322	325	—	332	332	—
BIC	338	339	—	348	346	—
ρ[95%CI]	− .58[− 1,−.074]	—	—	.057 [−.72,.83]	—	—
p(ρ)	.11	—	—	.5	—	—
N = 48
χ2[DF]	1.82 [2]	8.41 [3]	6.33 [1]	1.87 [2]	2.92 [3]	0.85 [1]
p(χ2)	.4	.04 *	.012 *	.39	.4	.36
RMSEA[95%CI]	.04 [.0001,.255]	.174 [.052,.334]	—	.042 [.0002,.257]	.042 [.0002,.224]	—
CFI	.992	.916	—	.994	.992	—
AIC	545	550	—	562	561	—
BIC	567	570	—	585	582	—
ρ[95%CI]	− .57[−.9,−.22]	—	—	.034 [−.52,.57]	—	—
p(ρ)	.04 *	—	—	.51	—	—
N = 80
χ2[DF]	1.84 [2]	12.32 [3]	10 [1]	1.84 [2]	2.84 [3]	1.04 [1]
p(χ2)	.4	.007 **	.0016 **	.4	.42	.37
RMSEA[95%CI]	.032 [.0001,.198]	.185 [.079,.308]	—	.032 [.0001,.198]	.031 [0,.17]	—
CFI	.995	.917	—	.997	.996	—
AIC	901	909	—	929	928	—
BIC	929	935	—	958	954	—
ρ[95%CI]	− .57[−.82,−.31]	—	—	.018 [−.39,.42]	—	—
p(ρ)	.004 **	—	—	.51	—	—
N = 300
χ2[DF]	1.8 [2]	38.2 [3]	36.17 [1]	1.77 [2]	2.78 [3]	0.81 [1]
p(χ2)	.41	< .001 ***	< .001 ***	.41	.42	.37
RMSEA[95%CI]	.016 [0,.101]	.196 [.143,.254]	—	.016 [0,.101]	.015 [0,.087]	—
CFI	.999	.915	—	.999	.999	—
AIC	334	338	—	345	345	—
BIC	339	342	—	349	349	—
ρ[95%CI]	− .57[−.69,−.44]	—	—	.0045 [−.19,.2]	—	—
p(ρ)	< .001 ***	—	—	.5	—	—

*p < .05, ** p < .01, *** p < .001