CRTConjoint-package: CRTConjoint: Conditional Randomization Testing (CRT) Approach...
In CRTConjoint: Conditional Randomization Testing (CRT) Approach for Conjoint Analysis
CRTConjoint-package R Documentation
CRTConjoint: Conditional Randomization Testing (CRT) Approach for Conjoint Analysis
Description
Computes p-value according to the CRT using the HierNet test statistic. For more details, see Ham, Imai, Janson (2022) "Using Machine Learning to Test Causal Hypotheses in Conjoint Analysis" arXiv:2201.08343.
Author(s)
Maintainer: Dae Woong Ham daewoongham@g.harvard.edu
Authors:
Kosuke Imai imai@harvard.edu
Lucas Janson ljanson@fas.harvard.edu
Other contributors:
Jacob Bien jbien@usc.edu [contributor, copyright holder]
See Also
Useful links:
CRTConjoint documentation built on June 9, 2022, 9:06 a.m.
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| CRTConjoint-package | R Documentation |
CRTConjoint: Conditional Randomization Testing (CRT) Approach for Conjoint Analysis
Description
Computes p-value according to the CRT using the HierNet test statistic. For more details, see Ham, Imai, Janson (2022) "Using Machine Learning to Test Causal Hypotheses in Conjoint Analysis" arXiv:2201.08343.
Author(s)
Maintainer: Dae Woong Ham daewoongham@g.harvard.edu
Authors:
Kosuke Imai imai@harvard.edu
Lucas Janson ljanson@fas.harvard.edu
Other contributors:
Jacob Bien jbien@usc.edu [contributor, copyright holder]
See Also
Useful links:
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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