An Introduction to Proximal Causal Inference-Reference-Cited by-同舟云学术

An Introduction to Proximal Causal Inference

Published:2024-08-01 Issue:3 Volume:39 Page:
ISSN:0883-4237
Container-title:Statistical Science
language:
Short-container-title:Statist. Sci.

Author:

Tchetgen Tchetgen Eric J.¹,Ying Andrew²,Cui Yifan³,Shi Xu⁴,Miao Wang⁵

Affiliation:

1. Eric J. Tchetgen Tchetgen is Professor in the Department of Statistics and Data Science, The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA

2. Andrew Ying is postdoctoral fellow in the Department of Statistics and Data Science, the Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA

3. Yifan Cui is Assistant Professor in the Center for Data Science and the School of Management, Zhejiang University, Hangzhou, China

4. Xu Shi is Assistant Professor in the Department of Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, USA

5. Wang Miao is Assistant Professor in the Department of Probability and Statistics, Peking University, Bejing, China

Publisher

Institute of Mathematical Statistics

Reference57 articles.

1. DAROLLES, S., FAN, Y., FLORENS, J. P. and RENAULT, E. (2011). Nonparametric instrumental regression. Econometrica 79 1541–1565.

2. HERNÁN, M. A. and ROBINS, J. M. (2006). Instruments for causal inference: An epidemiologist’s dream? Epidemiology 17 360–372.

3. HERNÁN, M. A. and ROBINS, J. M. (2020). Causal Inference: What If. CRC Press/CRC, Boca Raton, FL.

4. KUROKI, M. and PEARL, J. (2014). Measurement bias and effect restoration in causal inference. Biometrika 101 423–437.

5. MIAO, W., GENG, Z. and TCHETGEN TCHETGEN, E. J. (2018). Identifying causal effects with proxy variables of an unmeasured confounder. Biometrika 105 987–993.

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