Skip to main content

Publication bias and meta‐analysis for 2×2 tables: an average Markov chain Monte Carlo EM algorithm

Buy Article:

$43.00 plus tax (Refund Policy)

Summary. A major difficulty in meta‐analysis is publication bias. Studies with positive outcomes are more likely to be published than studies reporting negative or inconclusive results. Correcting for this bias is not possible without making untestable assumptions. In this paper, a sensitivity analysis is discussed for the meta‐analysis of 2×2 tables using exact conditional distributions. A Markov chain Monte Carlo EM algorithm is used to calculate maximum likelihood estimates. A rule for increasing the accuracy of estimation and automating the choice of the number of iterations is suggested.
No References
No Citations
No Supplementary Data
No Data/Media
No Metrics

Keywords: 2×2 table; EM algorithm; Funnel plots; Markov chain Monte Carlo methods; Meta‐analysis; Metropolis–Hastings algorithm; Publication bias; Sensitivity analysis

Document Type: Research Article

Affiliations: University of Glasgow, UK University of Warwick, Coventry, UK

Publication date: 2002-05-01

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more