G. Ellison

Statistics and Probability · 2017–2020

A researcher in the Science corpus: 2 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom G. Ellison trusts

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Sander Greenland (in Statistics and Probability)
  2. Johannes Textor (in Statistics and Probability)

Papers from G. Ellison's perspective

Ordered by how strongly the researchers G. Ellison trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Limitations of individual causal models, causal graphs, and ignorability assumptions, as illustrated by random confounding and design unfaithfulness
  2. The table 2 fallacy: presenting and interpreting confounder and modifier coefficients. (American Journal of Epidemiology)
  3. Causal Inference Using Potential Outcomes
  4. Kernel-based Conditional Independence Test and Application in Causal Discovery
  5. Understanding and misunderstanding randomized controlled trials (Social Science & Medicine (1967))
  6. An open graph visualization system and its applications to software engineering (Software, Practice & Experience)
  7. A Complete Generalized Adjustment Criterion
  8. DAGitty: a graphical tool for analyzing causal diagrams. (Epidemiology)
  9. Causal Inference in Statistics: A Primer
  10. Robust causal inference using directed acyclic graphs: the R package 'dagitty'. (International Journal of Epidemiology)

Their papers