Statistical analysis
SE
REGRESSION
We developed and validated two multivariable logistic regression models to predict BF after RP. We recalibrated the risk model in the validation cohort by matching logistic regression with the logit of the predictive risk We analyzed 95% confidence interval (CI) and SE values of prediction ability estimator in every predictive models, and the difference between the two models which from 2000 samples by stochastically selecting patients with substitution. We readjusted the prediction model and recalculated the prediction risk of every model in every sample in the research cohort. The 95% CIs came from 2.5% and 97.5% of the re-sampling distribution. Data for the resampling process included outcome (whether there was postoperative BF) and the unregulated predicted risk analyzed according to every risk models in the validation cohort. In every sample, the simple model for recalibration was readjusted, and then the predicted risk after calibration was recalculated. We compared variable distributions between research and validation cohorts. Categorical variables were assessed using χ