TSCI: Tools for Causal Inference with Possibly Invalid InstrumentalVariables
Two stage curvature identification with machine learning for causal inference in settings when instrumental variable regression is not suitable because of potentially invalid instrumental variables. Based on Guo and Buehlmann (2022) "Two Stage Curvature Identification with Machine Learning: Causal Inference with Possibly Invalid Instrumental Variables" <doi:10.48550/arXiv.2203.12808>. The vignette is available in Carl, Emmenegger, Bühlmann and Guo (2025) "TSCI: Two Stage Curvature Identification for Causal Inference with Invalid Instruments in R" <doi:10.18637/jss.v114.i07>.
| Version: | 3.0.5 |
| Depends: | R (≥ 4.0.0) |
| Imports: | xgboost,Rfast, stats,ranger, parallel,fastDummies |
| Suggests: | fda,MASS,testthat (≥ 3.0.0),withr |
| Published: | 2025-09-07 |
| DOI: | 10.32614/CRAN.package.TSCI |
| Author: | David Carl [aut, cre], Corinne Emmenegger [aut], Wei Yuan [aut], Mengchu Zheng [aut], Zijian Guo [aut] |
| Maintainer: | David Carl <david.carl at phd.unibocconi.it> |
| License: | GPL (≥ 3) |
| URL: | https://github.com/dlcarl/TSCI |
| NeedsCompilation: | no |
| Citation: | TSCI citation info |
| Materials: | README |
| CRAN checks: | TSCI results |
Documentation:
Downloads:
Linking:
Please use the canonical formhttps://CRAN.R-project.org/package=TSCIto link to this page.