Results 211 to 220 of about 1,239,696 (252)
Some of the next articles are maybe not open access.
Causal Inference: A Statistical Paradigm for Inferring Causality
2016Inferring causation is one important aim of many research studies across a wide range of disciplines. In this chapter, we will introduce the concept of potential outcomes for its application to causal inference as well as the basic concepts, models, and assumptions in causal inference.
Pan Wu +5 more
openaire +1 more source
Causal Inference with Large Language Model: A Survey
North American Chapter of the Association for Computational LinguisticsCausal inference has been a pivotal challenge across diverse domains such as medicine and economics, demanding a complicated integration of human knowledge, mathematical reasoning, and data mining capabilities.
Jing Ma
semanticscholar +1 more source
Prediction and causal inference
Acta Paediatrica, 2009Some months ago an interesting study by Olaf Dammann on ‘risk, predictability, and biomedical neo-pragmatism’ (1) appeared in these columns. Although I enjoyed his prose and agreed with many concepts, I believe that not enough emphasis was given on the difference between association and causation.
openaire +2 more sources
An Introduction to Causal Inference
1996Department of Philosophy technical ...
openaire +2 more sources
In this presentation, I provide a brief overview of quasiexperimental methods of estimating causal impacts using Stata: panel data, matching and reweighting, instrumental variables, and regression discontinuity designs, emphasizing practical ...
Ian D. Gow, Tongqing Ding
openaire +2 more sources
Inferring Hidden Causal Structure
Cognitive Science, 2010AbstractWe used a new method to assess how people can infer unobserved causal structure from patterns of observed events. Participants were taught to draw causal graphs, and then shown a pattern of associations and interventions on a novel causal system.
Tamar Kushnir +3 more
openaire +2 more sources
On Pearl’s Hierarchy and the Foundations of Causal Inference
Probabilistic and Causal Inference, 2022E. Bareinboim +3 more
semanticscholar +1 more source
Causal inference on discrete data
2020Kausale Inferenz ist eines der grundlegenden Probleme in der Wissenschaft. Um absolute Aussagen über Ursache und Wirkung zu treffen sind sorgfältig geplante Experimente notwendig, in denen wir repräsentative Populationen betrachten, die mutmaßliche Ursache messen und alle weiteren Umstände kontrollieren.
openaire +3 more sources
Causal inference for time series
Nature Reviews Earth & Environment, 2023Jakob Runge +4 more
semanticscholar +1 more source