Peter Jüni

Economics and Econometrics · 2001–2022

A researcher in the Science corpus: 35 papers; trusts 4 researchers and is trusted by 17 researchers here, as inferred from the citation graph.

Subfields

Whom Peter Jüni trusts overall

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

  1. David Moher
  2. Julian P. T. Higgins
  3. Douglas G. Altman
  4. J. Sterne
  5. K. F. Schulz
  6. Matthias Egger

Who trusts Peter Jüni overall

  1. Douglas G. Altman
  2. K. F. Schulz
  3. E. von Elm
  4. David Moher
  5. L. Mcfarland
  6. Julian P. T. Higgins
  7. Matthias Egger
  8. J. Barth
  9. J. Sterne
  10. Reza Kachouie

Papers from Peter Jüni's perspective

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

  1. How vague is vague? A simulation study of the impact of the use of vague prior distributions in MCMC using WinBUGS
  2. Systematic Review of the Empirical Evidence of Study Publication Bias and Outcome Reporting Bias (PLoS ONE)
  3. Systematic Review and Meta-analysis Supplements for Primary and Secondary Prevention: Mortality in Randomized Trials of Antioxidant
  4. CONSORT 2010 Explanation and Elaboration: updated guidelines for reporting parallel group randomised trials (British medical journal)
  5. Influence of reported study design characteristics on intervention effect estimates from randomised controlled trials: combined analysis of meta-epidemiological studies. (Health Technology Assessment)
  6. Is the placebo powerless? An analysis of clinical trials comparing placebo with no treatment. (New England Journal of Medicine)
  7. Observational studies analyzed like randomized experiments: an application to postmenopausal hormone therapy and coronary heart disease (Epidemiology)
  8. Using Big Data to Emulate a Target Trial When a Randomized Trial Is Not Available. (American Journal of Epidemiology)
  9. Quantifying heterogeneity in a meta‐analysis (Statistics in Medicine)
  10. C-reactive protein and other markers of inflammation in the prediction of cardiovascular disease in women. (New England Journal of Medicine)

Their papers