Yuyao Wang
I am a final year PhD student in mathematics with a specialization in statistics at University of California San Diego,
advised by Prof. Ronghui (Lily) Xu.
Before graduate school, I recieved my bachelor’s degree in mathematics from Xi’an Jiaotong University, China.
I also visited Georgia Institute of Technology and University of Alberta as a visiting student during my undergrad.
Email
GitHub
Google Scholar
CV
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Research
My methodology research interests include causal inference, survival analysis, missing data problems, semiparametric theory.
I am broadly interested in different topics in causal inference and missing data problems, especially in selection bias, heterogeneous treatment effects, balancing weighting, continuous treatment, and continuous time treatment.
I am also broadly interested in applications in health sciences, as well as social sciences such as education and psychology.
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Publications and Preprints
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- Yuyao Wang, Andrew Ying, Ronghui Xu. (2024)
Doubly robust estimation under covariate-induced dependent left truncation.
Biometrika, asae005, https://doi.org/10.1093/biomet/asae005
[pdf]
[code]
[R package]
(This paper won the student paper competition award for 2023 Lifetime Data Science Conference)
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Yingwei Peng, Yuyao Wang, Ronghui Xu. (2023)
Measures of explained variation under the mixture cure model for survival data.
Statistics in Medicine, 42(3), 228-245.
[pdf]
Working Papers
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- Yuyao Wang, Andrew Ying, Ronghui Xu. (2024+)
Learning treatment effects under covariate dependent left truncation and right censoring.
On arXiv soon.
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Lon R. White, Yuyao Wang, Lenore Launer, Lucia Seale, Marla Berry, Margaret Flannagan, Thomas J. Montine, Ronghui Xu.
(2024+)
Midlife dietary selenium and Okinawan ancestry are independently associated with less severe Alzheimer neuropathology at autopsy in Japanese-American men.
Submitted to Journal of Alzheimer's Disease.
R packages
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truncAIPW: Doubly Robust Estimation under Covariate-Induced Dependent Left Truncation
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aftR2: R-squared Measure under Accelerated Failure Time (AFT) Models
Presentations
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Learning treatment effects under covariate dependent left truncation and right censoring.
Presentation at 2024 Joint Statistical Meetings (JSM).
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Doubly robust estimation of treatment effects under covariate dependent left truncation and right censoring.
Poster at 2024 American Causal Inference Conference (ACIC).
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Learning Treatment Effects under Covariate Dependent Left Truncation and Right Censoring.
Presentation at 2024 Southern California Applied Mathematics Symposium (COCAMS).
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Doubly Robust Estimation under Covariate-induced Dependent Left Truncation.
Presentation at McGill Statistics Seminar (2023 Fall).
[slides]
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Doubly Robust Estimation under Covariate-induced Dependent Left Truncation.
Presentation at 2023 Joint Statistical Meetings (JSM).
[slides]
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Doubly Robust Estimation under Covariate-induced Dependent Left Truncation.
Presentation at 2023 Lifetime Data Science Conference (LiDS).
[slides]
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Multiply Robust Estimation of Treatment Effect for Time-to-event Outcome under Dependent Left Truncation.
Poster at 2023 American Causal Inference Conference (ACIC).
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Doubly Robust Estimation under Covariate-induced Dependent Left Truncation. Poster at 2023 Public Health Research Day at UCSD.
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Semiparametric Estimation for Non-randomly Truncated Data. Poster at 2022 American Causal Inference Conference (ACIC).
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Semiparametric Estimation for Non-randomly Truncated Data. Poster presented at 2022 Public Health Research Day at UCSD.
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