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Causal inference in perception
Trends in Cognitive Sciences, 2010Until recently, the question of how the brain performs causal inference has been studied primarily in the context of cognitive reasoning. However, this problem is at least equally crucial in perceptual processing. At any given moment, the perceptual system receives multiple sensory signals within and across modalities and, for example, has to determine
Ladan, Shams, Ulrik R, Beierholm
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Causal inference for clinicians
BMJ Evidence-Based Medicine, 2019Evidence-based medicine (EBM) calls on clinicians to incorporate the ‘best available evidence’ into clinical decision-making. For decisions regarding treatment, the best evidence is that which determines the causal effect of treatments on the clinical outcomes of interest.
Steven D Stovitz, Ian Shrier
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Causal Inference by Compression
2016 IEEE 16th International Conference on Data Mining (ICDM), 2016Causal inference is one of the fundamental problems in science. In recent years, several methods have been proposed for discovering causal structure from observational data. These methods, however, focus specifically on numeric data, and are not applicable on nominal or binary data. In this work, we focus on causal inference for binary data. Simply put,
Budhathoki, K., Vreeken, J.
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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
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An Introduction to Causal Inference
1996Department of Philosophy technical ...
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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.
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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
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A Simplified Logic of Causal Inference
Australian & New Zealand Journal of Psychiatry, 1987This paper provides a simplified method for evaluating the evidence in favour of a causal claim. It analyses the evidence bearing upon such a claim in terms of two questions: Do the putative cause and effect covary, and can alternative non-causal explanations of the relationship be ruled out? The different research designs for assessing covariation are
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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.
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