Sensitivity analysis in observational research: introducing the E-value TJ VanderWeele, P Ding Annals of Internal Medicine 167 (4), 268-274, 2017 | 3707 | 2017 |
Sensitivity analysis without assumptions P Ding, TJ VanderWeele Epidemiology (Cambridge, Mass.) 27 (3), 368, 2016 | 558 | 2016 |
Web site and R package for computing E-values MB Mathur, P Ding, CA Riddell, TJ VanderWeele Epidemiology 29 (5), e45-e47, 2018 | 543 | 2018 |
Overlap in observational studies with high-dimensional covariates A D’Amour, P Ding, A Feller, L Lei, J Sekhon Journal of Econometrics 221 (2), 644-654, 2021 | 230 | 2021 |
General forms of finite population central limit theorems with applications to causal inference X Li, P Ding Journal of the American Statistical Association 112 (520), 1759-1769, 2017 | 209 | 2017 |
Randomization inference for treatment effect variation P Ding, A Feller, L Miratrix Journal of the Royal Statistical Society, Series B (Statistical Methodology), 2014 | 157 | 2014 |
Causal Inference: A Missing Data Perspective P Ding, F Li Statistical Science 33 (2), 214-237, 2018 | 147 | 2018 |
To adjust or not to adjust? Sensitivity analysis of M-bias and butterfly-bias P Ding, LW Miratrix Journal of Causal Inference 3 (1), 41-57, 2015 | 139 | 2015 |
Causal inference K Kuang, L Li, Z Geng, L Xu, K Zhang, B Liao, H Huang, P Ding, W Miao, ... Engineering 6 (3), 253-263, 2020 | 123 | 2020 |
Asymptotic theory of rerandomization in treatment–control experiments X Li, P Ding, DB Rubin Proceedings of the National Academy of Sciences 115 (37), 9157-9162, 2018 | 119 | 2018 |
Principal stratification analysis using principal scores P Ding, J Lu Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2017 | 118 | 2017 |
Identifiability of normal and normal mixture models with nonignorable missing data W Miao, P Ding, Z Geng Journal of the American Statistical Association 111 (516), 1673-1683, 2016 | 111 | 2016 |
A paradox from randomization-based causal inference P Ding Statistical Science, 2017 | 105 | 2017 |
On the Conditional Distribution of the Multivariate t Distribution P Ding The American Statistician 70 (3), 293-295, 2016 | 94 | 2016 |
Decomposing treatment effect variation P Ding, A Feller, L Miratrix Journal of the American Statistical Association 114 (525), 304-317, 2019 | 93 | 2019 |
Technical considerations in the use of the E-value TJ VanderWeele, P Ding, M Mathur Journal of Causal Inference 7 (2), 20180007, 2019 | 92 | 2019 |
Identifiability and estimation of causal effects by principal stratification with outcomes truncated by death P Ding, Z Geng, W Yan, XH Zhou Journal of the American Statistical Association 106 (496), 2011 | 91 | 2011 |
A bracketing relationship between difference-in-differences and lagged-dependent-variable adjustment P Ding, F Li Political Analysis 27 (4), 605-615, 2019 | 86 | 2019 |
Combining multiple observational data sources to estimate causal effects S Yang, P Ding Journal of the American Statistical Association 115 (531), 1540-1554, 2020 | 85 | 2020 |
Rerandomization and regression adjustment X Li, P Ding Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2020 | 83 | 2020 |