E. von Elm

Statistics and Probability · 2007–2015

A researcher in the Science corpus: 14 papers; trusts 9 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

Whom E. von Elm trusts overall

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

  1. Douglas G. Altman
  2. David Moher
  3. Peter Jüni
  4. K. F. Schulz
  5. John P. A. Ioannidis
  6. Matthias Egger
  7. S. Evans
  8. M. Campbell
  9. Diana Elbourne
  10. Patrick M. M. Bossuyt

Who trusts E. von Elm overall

  1. Douglas G. Altman
  2. K. F. Schulz
  3. Jan Derks
  4. David Moher
  5. Gary S. Collins
  6. S. Cuschieri
  7. C. Tomasi
  8. Johannes B Reitsma
  9. Karel G. M. Moons
  10. T. L. Chu

Papers from E. von Elm's perspective

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

  1. Does the CONSORT checklist improve the quality of reports of randomised controlled trials? A systematic review (Medical Journal of Australia)
  2. Reducing waste from incomplete or unusable reports of biomedical research. (The Lancet)
  3. Dichotomizing continuous predictors in multiple regression: a bad idea (Statistics in Medicine)
  4. Empirical evidence for selective reporting of outcomes in randomized trials: comparison of protocols to published articles. (Journal of the American Medical Association (JAMA))
  5. Consolidated standards of reporting trials (CONSORT) and the completeness of reporting of randomised controlled trials (RCTs) published in medical journals. (Cochrane Database of Systematic Reviews)
  6. CONSORT 2010 Explanation and Elaboration: updated guidelines for reporting parallel group randomised trials (British medical journal)
  7. A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase. (American Journal of Human Genetics)
  8. Systematic Review of the Empirical Evidence of Study Publication Bias and Outcome Reporting Bias (PLoS ONE)
  9. [The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies]. (Revista Española de Salud Pública)
  10. How vague is vague? A simulation study of the impact of the use of vague prior distributions in MCMC using WinBUGS

Their papers