Causal inference and observational data
Iván Olier, Yiqiang Zhan, Xiaoyu Liang, Victor Volovici
Abstract
Observational studies using causal inference frameworks can provide a feasible alternative to randomized controlled trials. Advances in statistics, machine learning, and access to big data facilitate unraveling complex causal relationships from observational data across healthcare, social sciences, and other fields. However, challenges like evaluating models and bias amplification remain.
Topics & Concepts
Observational studyCausal inferenceData scienceInferenceRandomized experimentComputer scienceRandomized controlled trialStatistical inferencePsychologyEconometricsArtificial intelligenceMedicineStatisticsMathematicsSurgeryAdvanced Causal Inference TechniquesHealth Systems, Economic Evaluations, Quality of LifeStatistical Methods and Inference