Annals of Applied Statistics

Displaying 1 - 11 of 11
Mi, X., Bekerman, W., Rustgi, A. K., Sims, P. A., Canoll, P. D., & Hu, J. (2024). RZiMM-scRNA: A regularized zero-inflated mixture model framework for single-cell RNA-seq data. The Annals of Applied Statistics, 18(1). https://doi.org/10.1214/23-aoas1761
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Shen, J., Schwartz, J., Baccarelli, A. A., & Lin, X. (2024). Testing for the causal mediation effects of multiple mediators using the kernel machine difference method in genome-wide epigenetic studies. The Annals of Applied Statistics, 18(1). https://doi.org/10.1214/23-aoas1814
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Anthopolos, R., Chen, Q., Sedransk, J., Thompson, M., Meng, G., & Galea, S. (2023). A Bayesian growth mixture model for complex survey data: Clustering postdisaster PTSD trajectories. The Annals of Applied Statistics, 17(3). https://doi.org/10.1214/23-aoas1729
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Yao, Y., Ogden, R. T., Zeng, C., & Chen, Q. (2023). Bivariate hierarchical Bayesian model for combining summary measures and their uncertainties from multiple sources. The Annals of Applied Statistics, 17(2). https://doi.org/10.1214/22-aoas1699
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Cheung, Y. K., Chandereng, T., & Diaz, K. M. (2022). A novel framework to estimate multidimensional minimum effective doses using asymmetric posterior gain and ϵ-tapering. The Annals of Applied Statistics, 16(3). https://doi.org/10.1214/21-aoas1549
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Hu, L., Zou, J., Gu, C., Ji, J., Lopez, M., & Kale, M. (2022). A flexible sensitivity analysis approach for unmeasured confounding with multiple treatments and a binary outcome with application to SEER-Medicare lung cancer data. The Annals of Applied Statistics, 16(2). https://doi.org/10.1214/21-aoas1530
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Ling, W., Zhang, W., Cheng, B., & Wei, Y. (2021). Zero-inflated quantile rank-score based test (ZIQRank) with application to scRNA-seq differential gene expression analysis. The Annals of Applied Statistics, 15(4). https://doi.org/10.1214/21-aoas1442
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