TABLE 3.
Subjective well-being and alpha asymmetry, and covariates.
| Predictor variable | Estimate (SE) |
N (DF) | Model RMSE |
Model R2 |
Model F-statistic |
| α-asymmetry (Frontal) | |||||
| Age | −0.006* (0.002) | 218 (216) | 0.469 | 0.188 | 50*** |
| Gender_Male | 0.009 (0.071) | 214 (212) | 0.477 | 0.162 | 41*** |
| α-asymmetry (TP) | |||||
| Age | −0.009* (0.004) | 218 (216) | 0.819 | 0.026 | 5.76* |
| Gender_Male | 0.129 (0.123) | 214 (212) | 0.833 | 0.01 | 2.09 |
| Well-being | |||||
| Age | 0.258* (0.100) | 218 (216) | 19.7 | 0.031 | 7** |
| Gender_Male | 0.68 (2.914) | 214 (212) | 19.7 | 0.003 | 0.56 |
Column 2: p-values next to the Beta (β) coefficients and their standard error (SE) indicate a significant association between the predictor and the response variable at 95% confidence level (*), 99% confidence level (**) and 99.9% confidence level (***). Column 3: number of observations (N) and degrees of freedom (DF). Column 4–6: root mean square error (RMSE), R-squared, and F-statistic of the linear model. p-values next to F-statistic indicate a significant fit (see above for confidence levels). Each simple linear model follows the equation: Response variable ∼ 1 + predictor.