| On the reproducibility of psychological science VE Johnson, RD Payne, T Wang, A Asher, S Mandal Journal of the American Statistical Association 112 (517), 1-10, 2017 | 160 | 2017 |
| Sparse quadratic classification rules via linear dimension reduction I Gaynanova, T Wang Journal of Multivariate Analysis 169, 278-299, 2019 | 17 | 2019 |
| Categorizing a continuous predictor subject to measurement error BGB Achic, T Wang, Y Su, V Kipnis, K Dodd, RJ Carroll Electronic Journal of Statistics 12 (2), 4032-4056, 2018 | 9 | 2018 |
| A flexible zero-inflated poisson-gamma model with application to microbiome sequence count data R Jiang, X Zhan, T Wang Journal of the American Statistical Association 118 (542), 792-804, 2023 | 8 | 2023 |
| Integrated Quantile RAnk Test (iQRAT) for gene-level associations T Wang, I Ionita-Laza, Y Wei The Annals of Applied Statistics 16 (3), 1423-1444, 2022 | 6 | 2022 |
| The optimal pre-post allocation for randomized clinical trials S Ma, T Wang BMC Medical Research Methodology 23 (1), 72, 2023 | 5 | 2023 |
| Testing microbiome association using integrated quantile regression models T Wang, W Ling, AM Plantinga, MC Wu, X Zhan Bioinformatics 38 (2), 419-425, 2022 | 5 | 2022 |
| Gaussian Processes with Errors in Variables: Theory and Computation S Zhou, D Pati, T Wang, Y Yang, RJ Carroll https://arxiv.org/abs/1910.06235, 2019 | 5 | 2019 |
| Three‐part joint modeling methods for complex functional data mixed with zero‐and‐one–inflated proportions and zero‐inflated continuous outcomes with skewness H Li, J Staudenmayer, T Wang, SK Keadle, RJ Carroll Statistics in medicine 37 (4), 611-626, 2018 | 5 | 2018 |
| Integrated Quantile RAnk Test (iQRAT) for gene-level associations in sequencing studies T Wang, I Ionita-Laza, Y Wei https://arxiv.org/abs/1910.10102, 2019 | 4 | 2019 |
| Genome-wide discovery for biomarkers using quantile regression at biobank scale C Wang, T Wang, K Kiryluk, Y Wei, H Aschard, I Ionita-Laza Nature Communications 15 (1), 6460, 2024 | 3 | 2024 |
| Optimal Fingerprinting with Estimating Equations S Ma, T Wang, J Yan, X Zhang Journal of Climate 36 (20), 7109-7122, 2023 | 3 | 2023 |
| Gaussian processes with errors in variables: Theory and computation S Zhou, D Pati, T Wang, Y Yang, RJ Carroll Journal of Machine Learning Research 24 (87), 1-53, 2023 | 2 | 2023 |
| DAP: Discriminant Analysis via Projections T Wang, I Gaynanova R package, 2018 | 2 | 2018 |
| Extreme value modeling with errors-in-variables in detection and attribution of changes in climate extremes YTA Lau, T Wang, J Yan, X Zhang Statistics and Computing 33 (6), 125, 2023 | 1 | 2023 |
| Supplement to “Integrated Quantile RAnk Test (iQRAT) for gene-level associations.” T WANG, I IONITA-LAZA, Y WEI | 1 | 2022 |
| A unified quantile framework reveals nonlinear heterogeneous transcriptome-wide associations T Wang, I Ionita-Laza, Y Wei https://arxiv.org/pdf/2207.12081.pdf, 2022 | 1 | 2022 |
| Improved Semiparametric Analysis of Polygenic Gene–Environment Interactions in Case–Control Studies T Wang, A Asher Statistics in Biosciences 13, 386-401, 2021 | 1 | 2021 |
| Package ‘MiRKAT’ A Plantinga, N Wilson, H Zheng, T Wang, X Zhan, M Wu, N Zhao, J Chen | | 2025 |
| Debiased high-dimensional regression calibration for errors-in-variables log-contrast models H Zhao, T Wang Biometrics 80 (4), ujae153, 2024 | | 2024 |
Iuliana Ionita-LazaProfessor of Biostatistics, Columbia UniversityVerified email at columbia.edu