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Publication bias and meta‐analysis for 2×2 tables: an average Markov chain Monte Carlo EM algorithm
Author(s) -
Shi Jian Qing,
Copas John
Publication year - 2002
Publication title -
journal of the royal statistical society: series b (statistical methodology)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.523
H-Index - 137
eISSN - 1467-9868
pISSN - 1369-7412
DOI - 10.1111/1467-9868.00334
Subject(s) - markov chain monte carlo , monte carlo method , algorithm , markov chain , meta analysis , sensitivity (control systems) , statistics , computer science , mathematics , econometrics , medicine , electronic engineering , engineering
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.