Assumption-lean and Data-adaptive Post-Prediction Inference

A primary challenge facing modern scientific research is the limited availability of gold-standard data which can be both costly and labor-intensive to obtain. With the rapid development of machine learning (ML), scientists have relied on ML algorithms to predict these gold-standard outcomes with easily obtained covariates. However, these predicted outcomes are often used directly in subsequent statistical analyses, ignoring imprecision and heterogeneity introduced by the prediction procedure. This will likely result in false positive findings and invalid scientific conclusions. In …

algorithms availability challenge cs.lg data development inference labor lean machine machine learning ml algorithms modern prediction research scientific research scientists standard stat.me stat.ml