ML Anthology

Piecewise Linear Instrumental Variable Estimation of Causal Influence

Richard Scheines, Gregory F. Cooper, Changwon Yoo, Tianjiao Chu
AISTATS 2001 pp. 265-271
/aistats/2001/scheines2001aistats-piecewise/

Abstract

Instrumental Variable (IV) estimation is a powerful strategy for estimating causal influence, even in the presence of confounding. Standard IV estimation requires that the relationships between variables is linear. Here we relax the linearity requirement by constructing a piecewise linear IV estimator. Simulation studies show that when the causal influence of $X$ on $Y$ is non-linear, the piecewise linear is an improvement.

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Text

Scheines et al. "Piecewise Linear Instrumental Variable Estimation of Causal Influence." Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001.

Markdown

[Scheines et al. "Piecewise Linear Instrumental Variable Estimation of Causal Influence." Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001.](https://mlanthology.org/aistats/2001/scheines2001aistats-piecewise/)

BibTeX

@inproceedings{scheines2001aistats-piecewise,
  title     = {{Piecewise Linear Instrumental Variable Estimation of Causal Influence}},
  author    = {Scheines, Richard and Cooper, Gregory F. and Yoo, Changwon and Chu, Tianjiao},
  booktitle = {Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics},
  year      = {2001},
  pages     = {265-271},
  volume    = {R3},
  url       = {https://mlanthology.org/aistats/2001/scheines2001aistats-piecewise/}
}