Table 2 Hierarchical Multiple Regression for CMSA-Motor and ARAT.

	R²	Adjusted R²	p-value	β	p-value	ΔR²	p-value
*Chedoke-McMaster Stroke Assessment Impairment Inventory Total Motor Impairment (CMSA-Motor)*
Interaction Model	0.55	0.49	0.001			—	—
CST Injury				−0.48	0.004
LM1-RM1 rs-connectivity				0.60	0.001
Interaction				0.05	0.75
Additive Model	0.55	0.51	<0.001			−0.002^#	0.75
CST Injury				−0.48	0.003
LM1-RM1 rs-connectivity				0.58	<0.001
Simple Regression 1	0.21	0.18	0.02			−0.34^{^}	<0.001
CST Injury				−0.46	0.02
Simple Regression 2	0.32	0.29	0.003			−0.23^{^}	0.003
LM1-RM1 rs-connectivity				0.57	0.003
*Action Research Arm Test (ARAT)*
Interaction Model	0.44	0.36	0.006			—	—
CST Injury				−0.48	0.008
LM1-RM1 rs-connectivity				0.48	0.01
Interaction				0.04	0.81
Additive Model	0.44	0.39	0.002			−0.002^#	0.81
CST Injury				−0.49	0.006
LM1-RM1 rs-connectivity				0.47	0.008
Simple Regression 1	0.22	0.19	0.02			−0.22^{^}	0.008
CST Injury				−0.47	0.02
Simple Regression 2	0.20	0.17	0.02			−0.24^{^}	0.006
LM1-RM1 rs-connectivity				0.45	0.02

R², adjusted R², β-values, ΔR² values, and the associated significance (p-values) for the hierarchical multiple regression models to explain variability in performance on motor assessments. Hash (^#) represents the ΔR² value from the comparison between the interaction model and additive model. Caret (^{^}) represents the ΔR² value from the comparison between the additive model and simple regression model. Model comparisons are considered significant at p < 0.05.

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