We used SAS ( version 9.1 ) for univariable data analysis and to generate a multivariable logistic regression model . We used Student 's t test , Wilcoxon rank sum test , or χ 2 test for comparing characteristics in the study population and pregnancy outcomes between women who did and did not develop pre - eclampsia . Stepwise logistic regression was used to determine independent risk factors for pre - eclampsia in both datasets . The order of variable selection was determined by the χ 2 statistic for each potential variable and the forward selection step could be followed by removal of variables in one or more backward elimination steps . We calculated receiver operating characteristics curves and determined screening test characteristics at a 25 % , 10 % , and 5 % false positive rate . For internal validation we evaluated the calibration and discrimination ( 10 - fold cross validation ) of the model using methods described by Altman et al . 30 Calibration was assessed by plotting the observed proportion of events against the predicted probabilities . For the cross validation , participants were stratified by region ( New Zealand , Australia , Ireland , and UK ) , pre - eclampsia status ( positive or negative ) , and gestation ( < 260 days or ≥260 days ) and randomly allocated to one of 10 groups . Tenfold cross validation was then performed , with 90 % of the data used to generate a model , and estimation of disease risk was performed in the 10 % remaining . These predicted values were then combined across the 10 runs and summarised by the C statistic ( AUC ) . This entire procedure was repeated 10 times .