Table 6.

Model comparisons for the effects of lesion volume on motor outcome, Fugl-Meyer Arm score.

	Estimate	SE	t-Value	p-Value
Best fitting model parameters (based on Wald Test)
Intercept	18.21	1.81	10.07	< 0.001
Lesion rtVolume	0.002	0.003	0.85	0.40
Sex	− 3.50	1.56	− 2.25	0.03
Age	0.03	0.06	0.47	0.64
rtDSS	− 0.19	0.07	− 2.62	0.01
Best fitting model parameters (excluding Yin, 2012)
Intercept	19.30	1.39	13.86	< 0.001
Lesion rtVolume	0.003	0.002	1.11	0.27
Sex	− 2.24	1.54	− 1.45	0.15
Age	0.03	0.06	0.44	0.66
rtDSS	− 0.12	0.07	− 1.63	0.11

Note. The best fitting model included lesion volume, Sex, Age, Days Since Stroke (DSS; AIC = 605.4, BIC = 622.9, Wald Test p < 0.01) and was based on 89 individuals from 9 different studies. The fit of this model was a significant improvement beyond lesion volume alone (AIC = 611.8, BIC = 621.7). Sex was coded as female = 0·5, male = − 0·5; age was centred around overall mean age = 58·56; and DSS and lesion volume were square root transformed (rtDSS, rtVolume) and then centred around the root-transformed mean. This led to an approximately normal distribution of residuals and homoscedasticity of the residuals. Data from Yin (2012) exerted significant leverage on the model, and thus the model was rerun with these data excluded (AIC = 426.6; 441.8; based on 65 individuals from 8 different studies). Cook's distance for Yin (2012) was 0·51, which is greater than the ‘4/number of groups in the grouping factor’ recommended cut-off (i.e., 4/9 = 0.44; (Van der Meer et al., 2010) and thus was excluded in the final model. AIC Akaike information criterion. BIC Bayesian information criterion.