Scholar
Peng Ding
Google Scholar ID: 8AXJB5QAAAAJ
University of California, Berkeley
causal inference
experimental design
missing data
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Citations & Impact
All-time
Citations
10,292
H-index
39
i10-index
82
Publications
20
Co-authors
34
list available
Publications
10 items
Imputation is all you need: double robustness, semiparametric efficiency, and automatic covariate balance for estimating the average treatment effect
2026
Cited
0
Causal inference in two-sided randomization designs: factorial regression, two-way clustering, and covariate adjustment
2026
Cited
0
Misspecified regressions with mixed regressors: robust inference and causal interpretation
2026
Cited
0
Bracketing Relationships of Weighted Average Treatment Effects
2026
Cited
0
Estimating within-cluster and between-cluster spillover effects in randomized saturation designs
2026
Cited
0
Introducing the b-value: combining unbiased and biased estimators from a sensitivity analysis perspective
2026
Cited
0
Generative modeling for the bootstrap
2026
Cited
0
Decoupling and randomization for double-indexed permutation statistics
2026
Cited
0
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Co-authors
16 total
Xinran Li
Assistant professor at University of Chicago
Anqi Zhao
Assistant Professor, Duke University
Shu Yang
North Carolina State University
Avi Feller
UC Berkeley
Fan Li
Department of Statistical Science, Duke University
Jiannan Lu
Apple
Jasjeet Sekhon
Eugene Meyer Professor of Data Science, Political Science, and Statistics, Yale University
LIHUA LEI
Stanford University
