Causal inference of interaction effects with inverse propensity weighting, G-computation and tree-based standardization

2014 ◽  
Vol 7 (5) ◽  
pp. 323-336 ◽  
Author(s):  
Joseph Kang ◽  
Xiaogang Su ◽  
Lei Liu ◽  
Martha L. Daviglus
Keyword(s):  
Causal Inference ◽  
Interaction Effects ◽  
Inverse Propensity Weighting

Beyond metaphors and semantics: A framework for causal inference in neuroscience

2019 ◽  
Vol 42 ◽  
Author(s):  
Roberto A. Gulli
Keyword(s):  
Causal Inference ◽  
Causal Power

Abstract The long-enduring coding metaphor is deemed problematic because it imbues correlational evidence with causal power. In neuroscience, most research is correlational or conditionally correlational; this research, in aggregate, informs causal inference. Rather than prescribing semantics used in correlational studies, it would be useful for neuroscientists to focus on a constructive syntax to guide principled causal inference.

Imageability and Body-Object Interaction Effects in Multisyllabic Word Recognition

2011 ◽  
Author(s):  
Stephen D. R. Bennett ◽  
A. Nicole Burnett ◽  
Paul D. Siakaluk ◽  
Penny M. Pexman
Keyword(s):  
Word Recognition ◽  
Interaction Effects ◽  
Object Interaction

A Causal Inference Explanation for Multisensory Speech Perception

2013 ◽  
Author(s):  
John F. Magnotti ◽  
Wei Ji Ma ◽  
Michael S. Beauchamp
Keyword(s):  
Speech Perception ◽  
Causal Inference
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