Table 2.
Linear Regression Models Predicting Montreal Cognitive Assessment (z-standardized)
| Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | |
|---|---|---|---|---|---|
| β (SE) | β (SE) | β (SE) | β (SE) | β (SE) | |
| Sociodemographics | |||||
| Age | −0.02 (0.01) | −0.02 (0.01) | −0.02* (0.01) | −0.02 (0.01) | −0.02* (0.01) |
| Woman | 0.39* (0.15) | 0.33* (0.14) | 0.36** (0.14) | 0.31* (0.14) | 0.30* (0.15) |
| Education (years) | 0.08*** (0.02) | 0.07** (0.02) | 0.08*** (0.02) | 0.07*** (0.02) | 0.08*** (0.02) |
| White | 0.46** (0.15) | 0.43** (0.14) | 0.55*** (0.13) | 0.42** (0.14) | 0.42** (0.14) |
| Clinical measures | |||||
| GDS (logged) | −0.50*** (0.09) | −0.45*** (0.08) | −0.29*** (0.08) | −0.46*** (0.08) | −0.51*** (0.08) |
| Intracranial volume (z) | 0.12** (0.07) | 0.08 (0.08) | 0.06 (0.07) | 0.07 (0.08) | 0.05 (0.08) |
| Amygdalar atrophy (z) | −0.21* (0.08) | −0.19** (0.07) | −0.19** (0.07) | −0.45*** (0.13) | −0.43*** (0.11) |
| Network attributes | |||||
| Size | −0.03 (0.03) | −0.023 (0.03) | |||
| Prop. frequent contact | −0.61* (0.25) | −0.59** (0.22) | −0.48 (0.25) | −0.55* (0.25) | |
| Diversity | 0.12* (0.05) | 0.13* (0.05) | |||
| Effective size | 0.01 (0.04) | 0.03 (0.04) | |||
| Interactions | |||||
| Amygdala × Diversity | 0.08* (0.04) | ||||
| Amygdala × Effective size | 0.14* (0.05) | ||||
| Intercept | 0.23 (0.81) | −0.38 (0.84) | 0.51 (0.75) | −0.23 (0.82) | 0.79 (0.80) |
| Adjusted R 2 | 0.43 | 0.48 | 0.44 | 0.49 | 0.49 |
| N | 154 | 154 | 154 | 154 | 154 |
Notes: GDS = 15-item Geriatric Depression Scale. Models 3 and 5 do not control for network size because network size is a key component used to calculate effective size.
*p < .05, **p < .01, ***p < .001.