CRTConjoint: Conditional Randomization Testing (CRT) Approach for Conjoint
Analysis
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>.
| Version: |
0.1.0 |
| Depends: |
R (≥ 2.10) |
| Imports: |
utils, methods, doSNOW, foreach, Rcpp, snow |
| LinkingTo: |
Rcpp |
| Suggests: |
knitr, rmarkdown |
| Published: |
2022-06-09 |
| Author: |
Dae Woong Ham [aut, cre],
Kosuke Imai [aut],
Lucas Janson [aut],
Jacob Bien [ctb, cph] |
| Maintainer: |
Dae Woong Ham <daewoongham at g.harvard.edu> |
| BugReports: |
https://github.com/daewoongham97/CRTConjoint/issues |
| License: |
GPL (≥ 3) |
| Copyright: |
(c) 2022 Dae Woong Ham. Code in helper_hierNet.R, hierNet.c,
and hierNet_init.c are taken (with explicit permission) from
(c) 2020 Jacob Bien. |
| URL: |
https://github.com/daewoongham97/CRTConjoint |
| NeedsCompilation: |
yes |
| Materials: |
README NEWS |
| CRAN checks: |
CRTConjoint results |
Documentation:
Downloads:
Linking:
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