Table 2.
Regression table showing the final results of the logistic regression model
| Coefficient | Standard Error | z | P > |z| | 95% CI |
||
|---|---|---|---|---|---|---|
| Male sex | 1.1968 | 0.3090 | 3.87 | 0.000 | 0.5912 | 1.8023 |
| Sleepiness at the wheel | 0.7229 | 0.2791 | 2.59 | 0.010 | 0.1759 | 1.2699 |
| Bad sleep | 0.6423 | 0.3228 | 1.99 | 0.047 | 0.0096 | 1.2749 |
| Smoking | 1.1597 | 0.2829 | 4.10 | 0.000 | 0.6052 | 1.7143 |
| Constant | -2.8826 | 0.3399 | -8.48 | 0.000 | -3.5488 | -2.2163 |
| OR | Standard Error | z | P > |z| |
95% CI |
||
| Male sex | 3.3094 | 1.0225 | 3.87 | 0.000 | 1.8062 | 6.0639 |
| Sleepiness at the wheel | 2.0604 | 0.5750 | 2.59 | 0.010 | 1.1923 | 3.5604 |
| Bad sleep | 1.9008 | 0.6135 | 1.99 | 0.047 | 1.0097 | 3.5784 |
| Smoking | 3.1891 | 0.9024 | 4.10 | 0.000 | 1.8315 | 5.5530 |
Table 2 shows the coefficients (upper part) of each covariate (male sex, sleepiness at the wheel, bad sleep, smoking), and the odds ratios (OR) (lower part) in which the dependent outcome variable is self-reported car crash in the final logistic regression model.