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. Author manuscript; available in PMC: 2018 Sep 1.
Published in final edited form as: Neuroimage. 2017 Jun 21;158:90–98. doi: 10.1016/j.neuroimage.2017.06.044

Table 1.

Mean (SD) parameter estimates for each pathway type included in the individual structural equation model for each participant at each time and mean percentage of participants for whom the paths were significant. Aside from auto-regressive terms, contemporaneous paths accounted for the most variance in the model as indicated by higher parameter estimates compared to other pathway types. Additionally, contemporaneous pathways were the path type most likely to be significant in individual participant models, aside from auto-regressive terms.

Time 1 Time 2

Pathway Type Parameter Estimate Percent
Significant
Parameter Estimate Percent
Significant

Auto-regressive 0.39 (0.18) 92.8 0.40 (0.17) 94.5

Contemporaneous 0.25 (0.17) 77.6 0.20 (0.19) 73.2

Lagged −0.03 (0.13) 29.7 −0.04 (0.11) 26.7

Bilinear Interaction −0.01 (0.08) 7.1 −0.01 (0.12) 13.9

Input 0.08 (0.11) 13.6 0.07 (0.11) 12.7

Lagged Input −0.01 (0.10) 27.5 0.00 (0.10) 23.1