Table 3.
Multiple linear regression for environmental predictors only.
| Coeff. | SE | t-stat | lower t0.025(213) | upper t0.975(213) | Stand. Coeff. | P | VIF | |
|---|---|---|---|---|---|---|---|---|
| B | 3.00 | 0.100 | 30.0 | 2.80 | 3.19 | 0 | <0.00001 | |
| Log10(Pollen) | −0.0587 | 0.0144 | −4.08 | −0.0870 | −0.0303 | −0.167 | 0.0000633 | 1.56 |
| Log10(Solar radiation 7dma) | −0.592 | 0.0370 | −16.0 | −0.664 | −0.519 | −0.717 | <0.00001 | 1.89 |
| Dew point temperature | 0.00674 | 0.00109 | 6.19 | 0.00459 | 0.00888 | 0.235 | <0.00001 | 1.35 |
| Hay fever | −0.000262 | 0.0000903 | −2.91 | −0.000440 | −0.0000844 | −0.118 | 0.00405 | 1.56 |
Table 3: Overview of outcomes per selected environmental predictor after multiple linear regression. Selection of predictors is based on being (highly) significant and having multicollinearity (VIF) score below 2.5.