Question 4: Carry out a logistic regression using all three predictors of caesarean section. Do any of the predictors have an effect on the risk of a caesarean which is not explained by the other two?
Choose Analyze, Regression, Binary Logistic. Put the variable "Caesarian section" into Dependent and "BMI", "Induction of labour", and "Previous vaginal delivery" into Independent. Click OK.
We get a lot of output, ending with:
| Variables in the Equation | |||||||
|---|---|---|---|---|---|---|---|
| B | S.E. | Wald | df | Sig. | Exp(B) | ||
| Step 1a | bmi | .088 | .020 | 19.525 | 1 | .000 | 1.092 |
| iol | .647 | .214 | 9.139 | 1 | .003 | 1.910 | |
| prevag | -1.796 | .298 | 36.311 | 1 | .000 | .166 | |
| Constant | -3.700 | .534 | 47.953 | 1 | .000 | .025 | |
| a. Variable(s) entered on step 1: bmi, iol, prevag. | |||||||
All three variables have small P values and are highly significant. Hence there is strong evidence that each variable has an effect on the risk of caesarean independently of the other two.
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Last updated: 12 December, 2006.