For a full list of publications and a list of talks given by me, please see my cv: CV_cai.pdf
If you're interested in collaborating, please send me an email at xc2@williams.edu
Statistical Methodology:
Wang, Q. and Cai, X. (2025). A new perspective on U-Statistic variance estimation. Stat, 14: e70070. https://doi.org/10.1002/sta4.70070
Cai, X., Wang, Q., and Zhu, Y. (2023) ``Mediation Analysis with Latent Factors Using Simultaneous Group-wise and Parameter-wise Penalization'' Stat 12.1: e630. doi: https://doi.org/10.1002/sta4.630
Wang, J., Cai, X., Niu, X., and Li, R. (2023) Variable selection for high-dimensional nodal attributes in social networks with degree heterogeneity. Journal of the American Statistical Association, 1-14 .doi: https://doi.org/10.1080/01621459.2023.2187815k.
Cai, X., Coffman, D.L., Piper, M.E., and Li, R. (2022) Estimation and inference for the mediation effect in a time-varying mediation model. BMC Medical Research Methodology, 22, 113. doi: https://doi.org/10.1186/s12874-022-01585-x
Cai, X., Zhu, Y., Huang, Y., and Ghosh, D. (2022) High-dimensional causal mediation analysis based on partial linear structural equation models. Computational Statistics and Data Analysis, 107501. doi: https://doi.org/10.1016/j.csda.2022.107501
Wang, J., Cai, X., and Li, R. (2021) Variable selection for partially linear models via Bayesian subset modeling with diffusing prior. Journal of Multivariate Analysis, 104733. doi: https://doi.org/10.1016/j.jmva.2021.104733
Wang, Q., and Cai, X. (2021) An efficient variance estimator for cross-validation under partition sampling. Statistics, 55:3, 660-681. doi: https://doi.org/10.1080/02331888.2021.1943393
Coffman, D.L., Zhou, J. and Cai, X. (2020) Comparison of methods for handling covariate missingness in propensity score estimation with a binary exposure. BMC Medical Research Methodology, 20(1): 1-14. doi: https://doi.org/10.1186/s12874-020-01053-4
Coffman, D.L., Zhou, J., Cai, X. and Graham, J. (2018) Addressing missing data in confounders when estimating propensity scores for continuous exposures. Health Services and Outcomes Research Methodology, 18(4): 265-286. doi: https://doi.org/10.1007/s10742-018-0191-6
Luo, W. and Cai, X. (2016) A new estimator for efficient dimension reduction in regression. Journal of Multivariate Analysis, 145: 236-249. doi: https://doi.org/10.1016/j.jmva.2015.12.014
Collaborative Research on Applications:
Topaz, C.M., Garcia Nueva, B., Izidro de Souza, P., Schumann, J., Shvedova, L., Cai, X. and Ning, S. (2024). Race and Superfund Site Remediation. PNAS nexus, 3(9), page364, https://doi.org/10.1093/pnasnexus/pgae364
Coffman, D.L., Cai, X., Li, R. and Leonard, N.R. (2020) Challenges and opportunities in collecting and modeling ambulatory electrodermal activity data. JMIR Biomedical Engineering, 5(1): e17106. doi: https://doi.org/10.2196/17106
Fromm, D., Greenhouse, J., Hou, K., Russell, G.A., Cai, X., Forbes, M. and MacWhinney, B. (2016) Automated proposition density analysis for discourse in aphasia. Journal of Speech, Language, and Hearing Research, 59(5): 1123-1132. doi: https://doi.org/10.1044/2016_JSLHR-L-15-0401
Kaufer, D., Ishizaki, S., and Cai, X. (2016) Analyzing the language of citation across discipline and experience levels: an automated dictionary approach. Journal of Writing Research, 7(3): 453-483. doi: https://doi.org/10.17239/jowr-2016.07.03.07
Book:
Parry-Giles, S., Kaufer, D., and Cai, X. (2023) Hillary Clinton’s career in speeches: the promise and peril of women’s rhetorical adaptivity. Michigan State University Press (official released and will be available for purchase in September 2023)
Book project website: https://sites.google.com/view/hillary-clinton-speeches/
Statistics Education and Pedagogy:
Wang, Q., and Cai, X. (2023). Active-learning class activities and shiny applications for teaching support vector classifier. Journal of Statistics and Data Science Education. (accepted). doi: https://doi.org/10.1080/26939169.2023.2231065.
Wang, Q. and Cai, X. (2023) Online repository for facilitating teaching and learning of undergraduate statistical modeling tools. Proceedings of the international conference on higher education advances (HEAd), 631-638. http://dx.doi.org/10.4995/HEAD23.2023.16871.
Cai, X., and Wang, Q. (2020) Educational tool and active-learning class activity for teaching agglomerative hierarchical clustering. Journal of Statistics Education, 28(3), 280-288. doi: https://doi.org/10.1080/10691898.2020.1799727
R Package:
tvmediation (available on CRAN) estimation and inference for the time-varying mediation model