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AAAI
2011
13 years 13 days ago
Controlling Selection Bias in Causal Inference
Selection bias, caused by preferential exclusion of samples from the data, is a major obstacle to valid causal and statistical inferences; it cannot be removed by randomized exper...
Elias Bareinboim, Judea Pearl
SYNTHESE
2011
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13 years 7 months ago
Science without (parametric) models: the case of bootstrap resampling
Scientific and statistical inferences build heavily on explicit, parametric models, and often with good reasons. However, the limited scope of parametric models and the increasin...
Jan Sprenger
MANSCI
2011
13 years 7 months ago
Generating Ambiguity in the Laboratory
This article develops a method for drawing samples from which it is impossible to infer any quantile or moment of the underlying distribution. The method provides researchers with...
Jack Stecher, Timothy Shields, John Dickhaut