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THE IMPACT OF METHOD CHOICE ON META‐ANALYSIS
Author(s) -
Mengersen K.L.,
Tweedie R.L.,
Biggerstaff B.
Publication year - 1995
Publication title -
australian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 0004-9581
DOI - 10.1111/j.1467-842x.1995.tb00869.x
Subject(s) - meta analysis , econometrics , comparability , statistics , random effects model , logit , publication bias , confidence interval , mathematics , computer science , medicine , combinatorics
Summary This paper focusses mainly on three crucial choices identified in recent meta‐analyses, namely (a) the effect of using approximate statistical techniques rather than exact methods, (fa) the effect of using fixed or random effect models, and (c) the effect of publication bias on the meta‐analysis result. The paper considers their impact on a set of over thirty studies of passive smoking and lung cancer in non‐smokers, and addresses other issues such as the role of study comparability, the choice of raw or adjusted data when using published summary statistics, and the effect of biases such as misclassification of subjects and study quality. The paper concludes that, at least in this example, different conclusions might be drawn from metaanalyses based on fixed or random effect models; that exact methods might increase estimated confidence interval widths by 5–20% over standard approximate (logit and Mantel‐Haenszel) methods, and that these methods themselves differ by this order of magnitude; that taking study quality into account changes some results, and also improves homogeneity; that the use of unadjusted or author‐adjusted data makes limited difference; that there appears to be obvious publication bias favouring observed raised relative risks; and that the choice of studies for inclusion is the single most critical choice made by the modeller.