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Causal inference

Causal inference is the process of drawing a conclusion about a causal connection based on the conditions of the occurrence of an effect. The main… 
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Related topics

Related topics

11 relations
CausalityCorrelation does not imply causationMarginal structural modelPartial least squares regression

Broader (1)

Inductive reasoning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2019
2019
Democracy Does Cause Growth: Comment
I revisit the causal relationship between democracy and growth as recently studied in Acemoglu, Naidu, Restrepo, and Robinson… 
2015
2015
The Effect of Private Sector Work Opportunities in Prison on Labor Market Outcomes of the Formerly Incarcerated
This paper examines the effects of a private-sector prison work program called the Prison Industry Enhancement Certification… 
2014
2014
Some Aspects of Propensity Score-based Estimators for Causal Inference
In this paper, we show that a two-component normal mixture model provides a good approximation to the logistic distribution. This… 
2014
2014
Causal mechanism in transport collaboration
2014
2014
Increasing charitable giving in the developed world
Charitable giving has continued to increase in economic importance in the developed world. For instance, in the United States… 
2013
2013
Inheritance of Poverty or Inheritance of Place ? The Emerging Consensus on Neighborhoods and Stratification
Scholarly reputations that for a time seem unimpeachable now shrink or evaporate so speedily that ‘‘intergenerational… 
2013
2013
Composite Ontology-Based Medical Diagnosis Decision Support System Framework
Current medical decision support systems have evolved from the automation of medical decision routines to improving the quality… 
2012
2012
Rational RatsCausal Inference and Representation
2007
2007
Causal Graphical Models with Latent Variables: Learning and Inference
Several paradigms exist for modeling causal graphical models for discrete variables that can handle latent variables without… 
2000
2000
A Comparison of Association Rule Discovery and Bayesian Network Causal Inference Algorithms to Discover Relationships in Discrete Data
Association rules discovered through attribute-oriented induction are commonly used in data mining tools to express relationships… 
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