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Peng Ding

60 papers hereh-index 389.1k citations118 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author5
  • first author9
  • middle author13
  • last author33

Across the 60 of 60 papers where every author was matched, so the position is known.

fields
  • stat.ME37
  • math.ST15
  • stat.AP4
  • econ.EM2
  • cs.LG1
  • math.NT1
same name
  • Peng Ding — 7 papers, h 3
  • Peng Ding — 6 papers, h 1
  • Peng Ding — 5 papers, h 3
  • Peng Ding — 4 papers
  • Peng Ding — 4 papers, h 3
  • Peng Ding — 4 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20152026
most citedSensitivity Analysis Without Assumptions

12 citations · 61 across the 32 of their papers we have counts for

collaborators
Showing 2018 · stat.MEShow all

4 papers · 2 filters

stat.ME2018

Randomization Tests for Weak Null Hypotheses in Randomized Experiments

Jason Wu, Peng Ding

The Fisher randomization test (FRT) is appropriate for any test statistic, under a sharp null hypothesis that can recover all missing potential outcomes. However, it is often sough…

stat.ME2018

Randomization Inference for Peer Effects

Xinran Li, Peng Ding, Qian Lin +2

Many previous causal inference studies require no interference, that is, the potential outcomes of a unit do not depend on the treatments of other units. However, this no-interfere…

stat.ME2018★ 6 cited

Causal Inference: A Missing Data Perspective

Peng Ding, Fan Li

Inferring causal effects of treatments is a central goal in many disciplines. The potential outcomes framework is a main statistical approach to causal inference, in which a causal…

stat.ME2018

Combining multiple observational data sources to estimate causal effects

Shu Yang, Peng Ding

The era of big data has witnessed an increasing availability of multiple data sources for statistical analyses. We consider estimation of causal effects combining big main data wit…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.