D. Burke

Statistics and Probability · with Ensor · 2016–2018

A researcher in the Science corpus: 2 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom D. Burke trusts overall

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

  1. W. Viechtbauer
  2. R. Riley
  3. R. Dersimonian
  4. Dan Jackson
  5. Julian P. T. Higgins
  6. Raghu N. Kacker
  7. Ewout W. Steyerberg
  8. Guido Knapp
  9. Ian R. White
  10. H. V. van Houwelingen

Papers from D. Burke's perspective

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

  1. Random-effects model for meta-analysis of clinical trials: an update. (Contemporary Clinical Trials)
  2. The Hartung-Knapp-Sidik-Jonkman method for random effects meta-analysis is straightforward and considerably outperforms the standard DerSimonian-Laird method (BMC Medical Research Methodology)
  3. Improved tests for a random effects meta‐regression with a single covariate (Statistics in Medicine)
  4. Metaan: Random-effects Meta-analysis
  5. Much ado about nothing: a comparison of the performance of meta‐analytical methods with rare events (Statistics in Medicine)
  6. Multivariate meta-analysis: Potential and promise (Statistics in Medicine)
  7. Interpretation of random effects meta-analyses (British medical journal)
  8. Modern modelling techniques are data hungry: a simulation study for predicting dichotomous endpoints (BMC Medical Research Methodology)
  9. Value of assessment of pretest probability of deep-vein thrombosis in clinical management.
  10. Conducting Meta-Analyses in R with the metafor Package

Their papers