Preprints:
(Corresponding author* if not the first author)
Dingke Tang, Dehan Kong, and Linbo Wang*. The synthetic instrument: From sparse association to sparse causation. [arXiv] [R package]
Xinyi Zhang, Linbo Wang, Stanislav Volgushev, Dehan Kong. Fighting Noise with Noise: Causal Inference with Many Candidate Instruments. [arXiv]
Linbo Wang. On the homogeneity of measures for binary associations. [arXiv].
Yuexia Zhang, Jian Wang, Jiayi Shen, Jessica Galloway-Pena, Samuel Shelburne, Linbo Wang*, and Jianhua Hu*. Inverse Probability Weighting-based Mediation Analysis for Microbiome Data. [arXiv].
Linbo Wang, Yuexia Zhang, Thomas Richardson, and Xiao-Hua Zhou. Robust Estimation of Propensity Score Weights via Subclassification. [arXiv] [slides]
(Winner of ICHPS 2015 Student Travel Award)
Publications:
(Corresponding author* if not the first author)
Ying Zhou, Dingke Tang, Dehan Kong, and Linbo Wang* (2024+) . The Promises of Parallel Outcomes. Biometrika, to appear. [arXiv] [slides (long)] [slides (short)]
(Winner of IMS Hannan Graduate Student Travel Award 2021)
(Winner of ICSA Student Paper Award 2021)
Linbo Wang, Eric Tchetgen Tchetgen, Torben Martinussen, and Stijn Vansteelandt (2023). Instrumental variable estimation of the causal hazard ratio (with discussion). Biometrics,79(2), 539-550. [arXiv] [code] [slides]
Linbo Wang, Eric Tchetgen Tchetgen, Torben Martinussen, and Stijn Vansteelandt (2023). Rejoinder. Biometrics,79(2), 564-568. [arXiv]
Zhenhua Lin, Dehan Kong, and Linbo Wang* (2023). Causal Inference on Distribution Functions. Journal of the Royal Statistical Society: Series B, 85(2), 378-398. [arXiv] [journal] [slides] [video]
Dingke Tang, Dehan Kong, Wenliang Pan, and Linbo Wang* (2023). Ultra-high dimensional variable selection for doubly robust causal inference. Biometrics, 79(2), 903-914. [arXiv] [code] [slides]
Linbo Wang, Xiang Meng, Thomas Richardson, and James Robins (2023). Coherent modeling of longitudinal causal effects on binary outcomes. Biometrics, 79(2), 775-787. [arXiv] [journal] [data & code]
Fernando Hartwig, Linbo Wang, George Smith, and Neil Davies (2023). Average causal effect estimation via instrumental variables: the no simultaneous heterogeneity assumption. Epidemiology, 34(3), 325-332. [arXiv].
Yuexia Zhang, Peibei Shi, Zhongyi Zhu, Linbo Wang, and Annie Qu (2023). Weak signal identification and inference in penalized likelihood models for categorical responses. Statistica Sinica, 33, 759-786. [arXiv]
Michael Best, Sylvia Romanowska, Ying Zhou, Linbo Wang, Talia Leibovitz, Karin A. Onno, Shreya Jagtap, Christopher Bowie. (2023). Efficacy of remotely delivered evidence-based psychosocial treatments for schizophrenia-spectrum disorders: a series of systematic reviews and meta-analyses. Schizophrenia Bulletin, 49(4), 973–986.
Blair Bilodeau, Linbo Wang, and Daniel M. Roy (2022). Adaptively Exploiting d-Separators with Causal Bandits (oral presentation). Advances of Neural Information Processing Systems (NeurIPS). [arXiv]
Dengdeng Yu, Linbo Wang, Dehan Kong, Hongtu Zhu (2022). Mapping the Genetic-Imaging-Clinical Pathway with Applications to Alzheimer's Disease. Journal of the American Statistical Association, 117(540), 1656-1668. [arXiv][journal]
Dehan Kong, Shu Yang, and Linbo Wang* (2022). Identifiability of causal effects with multiple causes and a binary outcome. Biometrika, 109(1): 265-272. [arXiv] [journal]
Jiaqi Yin, Sonia Markes, Thomas Richardson, and Linbo Wang* (2022). Multiplicative Effect Modeling: The General Case. Biometrika, 109(2), 559-566. [arXiv][journal]
Fernando Hartwig, Linbo Wang, George Smith, and Neil Davies (2022). Homogeneity in the Instrument-exposure Association and Point Estimation Using Binary Instrumental Variables. Epidemiology, 33(6), 828-831. [arXiv] [journal]
Julien Pierre, Xinyi Zhang, Tianyuan Lu, Lai Jiang, Xavier Loffree, Linbo Wang*, Sahir Bhatnagar*, Celia Greenwood* (2022). Considering strategies for SNP selection in genetic and polygenic risk scores. Frontiers in Genetics, 3005. [journal]
Linbo Wang, Yuexia Zhang, Thomas Richardson, and James Robins (2021). Estimation of local treatment effects under the binary instrumental variable model. Biometrika, 108(4), 881-894. [arXiv] [journal] [code]
Gintare Karolina Dziugaite, Alexandre Drouin, Brady Neal, Nitarshan Rajkumar, Ethan Caballero, Linbo Wang, Ioannis Mitliagkas, and Daniel Roy (2020). In Search of Robust Measures of Generalization. Advances of Neural Information Processing Systems 33 (NeurIPS). [arXiv]
Yuexia Zhang and Linbo Wang* (2020). Conditional Independence Beyond Domain Separability: Discussion of Engelke and Hitz (2020). Journal of the Royal Statistical Society: Series B, 82(4), 927-928. [arXiv]
Yue Wang and Linbo Wang (2020). Causal inference in degenerate systems: An impossibility result. International Conference on Artificial Intelligence and Statistics (AISTATS). [arXiv]
Shu Yang, Linbo Wang, and Peng Ding (2019). Causal inference with confounders missing not at random. Biometrika, 106(4): 875-888. [arXiv] [slides]
Linbo Wang and Eric Tchetgen Tchetgen (2018). Bounded, Efficient and Multiply Robust Estimation of Average Treatment Effects Using Instrumental Variables. Journal of the Royal Statistical Society: Series B, 80(3), 531-550. [arXiv] [data & code] [slides]
Thomas Richardson, James Robins, and Linbo Wang (2018). Discussion of "Data-Driven Confounder Selection via Markov and Bayesian Networks" by Haggstrom J. Biometrics, 74(2), 403-406. [arXiv]
Eric Tchetgen Tchetgen, Linbo Wang, and Baoluo Sun (2018). Discrete Choice Models for Nonmonotone Nonignorable Missing Data: Identification and Inference. Statistica Sinica, 28(4), 2069-2088. [arXiv]
Jessica Marden, Linbo Wang, Eric Tchetgen Tchetgen, Stefan Walter, Maria Glymour, and Kathleen Wirth (2018). Implementation of Instrumental Variable Bounds for Data Missing Not at Random. Epidemiology, 29(3), 364-368. [journal]
Thomas Richardson, James Robins, and Linbo Wang* (2017). On Modeling and Estimation for the Relative Risk and Risk Difference. Journal of the American Statistical Association: Theory and Methods, 519, 1121-1130. [arXiv] [slides (long)] [slides (short)] [poster]
R package brm
Linbo Wang, Thomas Richardson, and Xiao-Hua Zhou (2017). Causal Analysis of Ordinal Treatments and Binary Outcomes under Truncation by Death. Journal of the Royal Statistical Society: Series B, 79(3), 719–735. [arXiv] [slides] [poster]
Linbo Wang, Xiao-Hua Zhou, and Thomas Richardson (2017). Identification and Estimation of Causal Effects with Outcomes Truncated by Death. Biometrika, 104(3): 597-612. [arXiv]
R package tbd
Linbo Wang, James Robins, and Thomas Richardson (2017). On Falsification of the Binary Instrumental Variable Model. Biometrika, 104(1): 229-236. [arXiv] [slides]
Linbo Wang and Thomas Richardson (2017). On the Concordant Survivorship Assumption. Statistics in Medicine, 36(4), 717-720. [arXiv]
Linbo Wang, Shizhe Chen, and Ali Shojaie (2016). Comment on "Causal Inference Using Invariant Prediction: Identification and Confidence Intervals" by Peters, J., Buhlmann, P. and Meinshausen, N.. Journal of the Royal Statistical Society: Series B, 78, 1004-1005. [journal]
Yuhai Zhang, Xiao-Hua Zhou, Dana Meranus, Linbo Wang, and Walter Kukull (2016). Benzodiazepine Use and Cognitive Decline in Elderly With Normal Cognition. Alzheimer Disease & Associated Disorders, 30(2), 113-117. [journal]
Linbo Wang, Xiao-Hua Zhou, and Walter Kukull (2013). Are Some Individuals Immune to Dementia? Alzheimer's & Dementia: The Journal of the Alzheimer's Association, 9.4: P617-P618. [journal]
Preliminary results covered in Neurology Reviews (2013), 21(9):13.
Quan Wang, Linbo Wang, Minping Qian, and Minghua Deng (2010). A Hybridization Model for Tiling Array Analysis. In Bioinformatics and Biomedicine Workshops (BIBMW), 2010 IEEE International Conference on (pp. 148-151). IEEE. [conference]
Non-refereed Contributions:
Dehan Kong and Linbo Wang* (2023). Report: New Researchers Conference 2023. IMS Bulletin (2013), 52(7):20. [journal]