Nonparametric Adjustment for Measurement Error in Time-to-Event Data: Application to Risk Prediction Models
事件发生时间测量误差的非参数校正:风险预测模型应用
Mismeasured time to event data used as a predictor in risk prediction models will lead to inaccurate predictions. This arises in the context of self-reported family history, a time to event predictor often measured with error, used in Mendelian risk prediction models. Using validation data, we propose a method to adjust for this type of error. We estimate the measurement error process using a nonparametric smoothed Kaplan-Meier estimator, and use Monte Carlo integration to…