arbiter
JournalsAccount

TSCI: Two Stage Curvature Identification for Causal Inference with Invalid Instruments in R

David Carl et al.

Journal of Statistical Software2025https://doi.org/10.18637/jss.v114.i07article
ABDC A
Weight
0.37

Abstract

TSCI implements treatment effect estimation from observational data under invalid instruments in the R statistical computing environment. Existing instrumental variable approaches rely on arguably strong and untestable identification assumptions, which limits their practical application. TSCI does not require the classical instrumental variable identification conditions and is effective even if all instruments are invalid. TSCI implements a two-stage algorithm. In the first stage, machine learning is used to cope with nonlinearities and interactions in the treatment model. In the second stage, a space to capture the instrument violations is selected in a data-adaptive way. These violations are then projected out to estimate the treatment effect.

1 citation

Open via your library →

Cite this paper

https://doi.org/https://doi.org/10.18637/jss.v114.i07

Or copy a formatted citation

@article{david2025,
  title        = {{TSCI: Two Stage Curvature Identification for Causal Inference with Invalid Instruments in R}},
  author       = {David Carl et al.},
  journal      = {Journal of Statistical Software},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.18637/jss.v114.i07},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

TSCI: Two Stage Curvature Identification for Causal Inference with Invalid Instruments in R

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.