Effect Size

Effect size quantifies the magnitude of an effect or relationship in a study, crucial for interpreting research findings and ensuring reliable conclusions. Current research emphasizes improving effect size estimation across diverse methodologies, including developing new techniques for interpretable bias measurement in AI models (like ML-EAT) and addressing challenges in accurately estimating effect sizes in complex settings such as human-AI collaborations and online experiments. These advancements enhance the rigor and transparency of scientific research, leading to more robust and reliable inferences across various fields, from psychology and education to causal inference and machine learning.