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Peng Ding - Publications

Affiliations: 
Statistics University of California, Berkeley, Berkeley, CA, United States 
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36 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2020 Yang S, Ding P. Combining Multiple Observational Data Sources to Estimate Causal Effects. Journal of the American Statistical Association. 115: 1540-1554. PMID 33088006 DOI: 10.1080/01621459.2019.1609973  0.336
2020 Li X, Ding P, Rubin DB. Rerandomization in $2^{K}$ factorial experiments The Annals of Statistics. 48: 43-63. DOI: 10.1214/18-Aos1790  0.392
2020 Li X, Ding P. Rerandomization and regression adjustment Journal of the Royal Statistical Society Series B-Statistical Methodology. 82: 241-268. DOI: 10.1111/Rssb.12353  0.348
2020 Wu J, Ding P. Randomization Tests for Weak Null Hypotheses in Randomized Experiments Journal of the American Statistical Association. 1-16. DOI: 10.1080/01621459.2020.1750415  0.307
2020 D’Amour A, Ding P, Feller A, Lei L, Sekhon J. Overlap in observational studies with high-dimensional covariates Journal of Econometrics. DOI: 10.1016/J.Jeconom.2019.10.014  0.358
2019 Lu J, Zhang Y, Ding P. Sharp bounds on the relative treatment effect for ordinal outcomes. Biometrics. PMID 31742664 DOI: 10.1111/Biom.13148  0.382
2019 Ding P, Miratrix LW. Model‐free causal inference of binary experimental data Scandinavian Journal of Statistics. 46: 200-214. DOI: 10.1111/Sjos.12343  0.405
2019 Yang S, Wang L, Ding P. Causal inference with confounders missing not at random Biometrika. 106: 875-888. DOI: 10.1093/Biomet/Asz048  0.413
2019 Li X, Ding P, Lin Q, Yang D, Liu JS. Randomization Inference for Peer Effects Journal of the American Statistical Association. 114: 1651-1664. DOI: 10.1080/01621459.2018.1512863  0.366
2019 Ding P, Li F. A Bracketing Relationship between Difference-in-Differences and Lagged-Dependent-Variable Adjustment Political Analysis. 27: 605-615. DOI: 10.1017/Pan.2019.25  0.383
2018 Li X, Ding P, Rubin DB. Asymptotic theory of rerandomization in treatment-control experiments. Proceedings of the National Academy of Sciences of the United States of America. PMID 30150408 DOI: 10.1073/Pnas.1808191115  0.395
2018 Lu J, Ding P, Dasgupta T. Treatment Effects on Ordinal Outcomes: Causal Estimands and Sharp Bounds. Journal of Educational and Behavioral Statistics. 43: 540-567. DOI: 10.3102/1076998618776435  0.379
2018 Ding P, Li F. Causal Inference: A Missing Data Perspective Statistical Science. 33: 214-237. DOI: 10.1214/18-Sts645  0.393
2018 Zhao A, Ding P, Mukerjee R, Dasgupta T. Randomization-based causal inference from split-plot designs Annals of Statistics. 46: 1876-1903. DOI: 10.1214/17-Aos1605  0.397
2018 Forastiere L, Mattei A, Ding P. Principal ignorability in mediation analysis: through and beyond sequential ignorability Biometrika. 105: 979-986. DOI: 10.1093/Biomet/Asy053  0.402
2018 Yang S, Ding P. Asymptotic inference of causal effects with observational studies trimmed by the estimated propensity scores Biometrika. 105: 487-493. DOI: 10.1093/Biomet/Asy008  0.314
2018 Ding P, Dasgupta T. A randomization-based perspective on analysis of variance: a test statistic robust to treatment effect heterogeneity Biometrika. 105: 45-56. DOI: 10.1093/Biomet/Asx059  0.348
2017 Ding P, VanderWeele TJ, Robins JM. Instrumental variables as bias amplifiers with general outcome and confounding. Biometrika. 104: 291-302. PMID 29033459 DOI: 10.1093/Biomet/Asx009  0.417
2017 VanderWeele TJ, Ding P. Sensitivity Analysis in Observational Research: Introducing the E-Value. Annals of Internal Medicine. PMID 28693043 DOI: 10.7326/M16-2607  0.344
2017 Ding P. A Paradox from Randomization-Based Causal Inference Statistical Science. 32: 331-345. DOI: 10.1214/16-Sts571  0.377
2017 Ding P, Lu J. Principal stratification analysis using principal scores Journal of the Royal Statistical Society Series B-Statistical Methodology. 79: 757-777. DOI: 10.1111/Rssb.12191  0.413
2017 Li X, Ding P. General Forms of Finite Population Central Limit Theorems with Applications to Causal Inference Journal of the American Statistical Association. 112: 1759-1769. DOI: 10.1080/01621459.2017.1295865  0.343
2016 Ding P, Vanderweele TJ. Sharp sensitivity bounds for mediation under unmeasured mediator-outcome confounding. Biometrika. 103: 483-490. PMID 27279672 DOI: 10.1093/Biomet/Asw012  0.34
2016 Li X, Ding P. Exact confidence intervals for the average causal effect on a binary outcome. Statistics in Medicine. PMID 26924519 DOI: 10.1002/Sim.6924  0.362
2016 Ding P, VanderWeele T. Sensitivity Analysis Without Assumptions. Epidemiology (Cambridge, Mass.). PMID 26841057 DOI: 10.1097/Ede.0000000000000457  0.357
2016 Jiang Z, Ding P, Geng Z. Principal causal effect identification and surrogate end point evaluation by multiple trials Journal of the Royal Statistical Society Series B-Statistical Methodology. 78: 829-848. DOI: 10.1111/Rssb.12135  0.36
2016 Miao W, Ding P, Geng Z. Identifiability of Normal and Normal Mixture Models with Nonignorable Missing Data Journal of the American Statistical Association. 111: 1673-1683. DOI: 10.1080/01621459.2015.1105808  0.33
2016 Ding P, Dasgupta T. A Potential Tale of Two-by-Two Tables From Completely Randomized Experiments Journal of the American Statistical Association. 111: 157-168. DOI: 10.1080/01621459.2014.995796  0.4
2015 Chen H, Ding P, Geng Z, Zhou XH. Semiparametric inference of the complier average causal effect with nonignorable missing outcomes Acm Transactions On Intelligent Systems and Technology. 7. DOI: 10.1145/2668135  0.408
2015 Ding P, Feller A, Miratrix L. Randomization inference for treatment effect variation Journal of the Royal Statistical Society. Series B: Statistical Methodology. DOI: 10.1111/Rssb.12124  0.367
2015 Lu J, Ding P, Dasgupta T. Construction of alternative hypotheses for randomization tests with ordinal outcomes Statistics and Probability Letters. 107: 348-355. DOI: 10.1016/J.Spl.2015.09.013  0.36
2014 Ding P, Geng Z. Identifiability of subgroup causal effects in randomized experiments with nonignorable missing covariates. Statistics in Medicine. 33: 1121-33. PMID 24122906 DOI: 10.1002/Sim.6014  0.358
2014 Ding P, Vanderweele TJ. Generalized Cornfield conditions for the risk difference Biometrika. 101: 971-977. DOI: 10.1093/Biomet/Asu030  0.302
2014 Ding P. Bayesian robust inference of sample selection using selection-t models Journal of Multivariate Analysis. 124: 451-464. DOI: 10.1016/J.Jmva.2013.11.014  0.315
2011 Ding P, Geng Z, Yan W, Zhou X. Identifiability and Estimation of Causal Effects by Principal Stratification With Outcomes Truncated by Death Journal of the American Statistical Association. 106: 1578-1591. DOI: 10.1198/Jasa.2011.Tm10265  0.393
2011 Yan W, Ding P, Geng Z, Zhou X. Identifiability of causal effects on a binary outcome within principal strata Frontiers of Mathematics in China. 6: 1249-1263. DOI: 10.1007/S11464-011-0127-8  0.361
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