Peng Ding

Citata da

	Tutte	Dal 2016
Citazioni	2599	2547
Indice H	21	21
i10-index	35	35

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201520162017201820192020202127 95 143 385 610 1043 248

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Tyler J. VanderWeeleJohn L. Loeb and Frances Lehman Loeb Professor of Epidemiology, Harvard UniversityEmail verificata su hsph.harvard.edu
Xinran LiAssistant professor at University of Illinois at Urbana-ChampaignEmail verificata su illinois.edu
Luke MiratrixHarvard UniversityEmail verificata su stat.harvard.edu
Zhichao JiangUniversity of Massachusetts AmherstEmail verificata su umass.edu
Tirthankar DasguptaRutgers UniversityEmail verificata su rutgers.edu
Avi FellerUC BerkeleyEmail verificata su berkeley.edu
Jiannan LuMicrosoft CorporationEmail verificata su microsoft.com
Shu YangNorth Carolina State UniversityEmail verificata su ncsu.edu
Fan LiDepartment of Statistical Science, Duke UniversityEmail verificata su duke.edu
LIHUA LEIPostdoctoral researcher in statistics, Stanford UniversityEmail verificata su stanford.edu
Corinne A RiddellUC BerkeleyEmail verificata su berkeley.edu
Donald B RubinYCMS Tsinghua; Senior Research Fellow at Fox / Temple U, Emeritus at Harvard UEmail verificata su temple.edu
XH ZhouProfessor of Biostatistics, University of WashingtonEmail verificata su u.washington.edu
Jasjeet SekhonEugene Meyer Professor of Data Science, Political Science, and Statistics, Yale UniversityEmail verificata su yale.edu
Alexander D'AmourResearch Scientist, Google BrainEmail verificata su google.com
Wang MiaoPeking UniversityEmail verificata su pku.edu.cn
James M. Robinsprofessor of epidemiology and biostatistics harvard school of public healthEmail verificata su hsph.harvard.edu
Linbo WangUniversity of TorontoEmail verificata su utoronto.ca
Christopher BailProfessor of Sociology and Public Policy, Duke UniversityEmail verificata su duke.edu
Friedolin MerhoutUniversity of CopenhagenEmail verificata su soc.ku.dk

Peng Ding

University of California, Berkeley

Email verificata su berkeley.edu - Home page

causal inference experimental design missing data


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
Sensitivity analysis in observational research: introducing the E-value TJ VanderWeele, P Ding Annals of Internal Medicine 167 (4), 268-274, 2017	1078	2017
Sensitivity analysis without assumptions P Ding, TJ VanderWeele Epidemiology (Cambridge, Mass.) 27 (3), 368, 2016	260	2016
Web site and R package for computing E-values MB Mathur, P Ding, CA Riddell, TJ VanderWeele Epidemiology 29 (5), e45-e47, 2018	121	2018
Randomization inference for treatment effect variation P Ding, A Feller, L Miratrix Journal of the Royal Statistical Society, Series B (Statistical Methodology), 2014	82	2014
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	74	2017
A paradox from randomization-based causal inference P Ding Statistical Science, 2017	65	2017
Overlap in observational studies with high-dimensional covariates A D’Amour, P Ding, A Feller, L Lei, J Sekhon Journal of Econometrics, 2020	62	2020
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	62	2015
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	55	2016
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	52	2011
On the Conditional Distribution of the Multivariate t Distribution P Ding The American Statistician 70 (3), 293-295, 2016	48	2016
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	47	2018
Principal stratification analysis using principal scores P Ding, J Lu Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2017	43	2017
Causal inference: A missing data perspective P Ding, F Li Statistical Science 33 (2), 214-237, 2018	41	2018
Sharp sensitivity bounds for mediation under unmeasured mediator-outcome confounding P Ding, TJ Vanderweele Biometrika 103 (2), 483-490, 2016	34	2016
Decomposing treatment effect variation P Ding, A Feller, L Miratrix Journal of the American Statistical Association 114 (525), 304-317, 2019	31	2019
A Potential Tale of Two-by-Two Tables From Completely Randomized Experiments P Ding, T Dasgupta Journal of the American Statistical Association 111 (513), 157-168, 2016	30	2016
Bayesian robust inference of sample selection using selection-t models P Ding Journal of Multivariate Analysis 124, 451-464, 2014	28	2014
Asymptotic causal inference with observational studies trimmed by the estimated propensity scores S Yang, P Ding Biometrika 105 (2), 487-493, 2018	24*	2018
Instrumental variables as bias amplifiers with general outcome and confounding P Ding, TJ Vanderweele, JM Robins Biometrika 104 (2), 291-302, 2017	23	2017

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