Conveners
SIS Invited session: Stratification, subsampling, randomization,issues and proposals
- Rossella Berni (Department of Statistics, Computer Science, Applications -University of Florence)
Description
SIS Invited session
Supervised learning under measurement constraints presents a challenge in the field of machine learning. In this scenario, while predictor observations are available, obtaining response observations is arduous or cost-prohibitive. Consequently, the optimal approach involves selecting a subset of predictor observations, acquiring the corresponding responses, and subsequently training a...
After a rich history in medicine, randomized control trials (RCTs), both simple and complex, are in increasing use in other areas, such as web-based A/B testing and planning and design of decisions. A main objective of RCTs is to be able to measure parameters, and contrasts in particular, while guarding against biases from hidden confounders. After careful definitions of classical entities...
Stratification on important variables is a common practice in clinical trials,
since ensuring cosmetic balance on known baseline covariates is often deemed to be a crucial requirement for the credibility of the experimental results. However, the actual benefits of stratification are still debated in the literature. Other authors have shown that it does not improve efficiency in large samples...