Table 6.
Regression model results with the ridership ratio as the dependent variable and the daily number of new COVID-19 cases as the independent variable. Model 1: ridership ratio of the whole system; Model 2: ridership ratio inside the subway's catchment area; Model 3: ridership ratio outside the subway's catchment area.
| Coef. | Std. Error | Significance | 95% CI | |
|---|---|---|---|---|
| Model 1 | ||||
| Constant | 4.706 | 0.212 | p < .001 | [4.271; 5.141] |
| Ln (COVID-19 cases) | −0.114 | 0.032 | p = .001 | [−0.179; −0.048] |
| Adj. R2 | 0.288 | Durbin-Watson | 1.954 | |
| N | 30 | VIF | 1.000 | |
| Model 2 | ||||
| Constant | 4.753 | 0.220 | p < .001 | [4.301; 5.204] |
| Ln (COVID-19 cases) | −0.147 | 0.033 | p < .001 | [−0.215; −0.079] |
| Adj. R2 | 0.393 | Durbin-Watson | 1.867 | |
| N | 30 | VIF | 1.000 | |
| Model 3 | ||||
| Constant | 4.678 | 0.211 | p < .001 | [4.246; 5.110] |
| Ln (COVID-19 cases) | −0.073 | 0.032 | p = .029 | [−0.138; −0.008] |
| Adj. R2 | 0.130 | Durbin-Watson | 2.005 | |
| N | 30 | VIF | 1.000 | |