Leveraging LLMs to Improve Experimental Design: A Generative Stratification Approach
利用大语言模型改善实验设计：生成式分层方法
Pre-experiment stratification, or blocking, is a well-established technique for designing more efficient experiments and increasing the precision of the experimental estimates. However, when researchers have access to many covariates at the experiment design stage, they often face challenges in effectively selecting or weighting covariates when creating their strata. This paper proposes a Generative Stratification procedure that leverages Large Language Models (LLMs) to…