A statistician looks at met-analysis.
I begin by considering origins and meanings for the term met-analysis/meta-analysis. The underlying ideas have a long history, not only in medical but also in the agricultural and social sciences. Met-analysis is a form of critical review of research on a stated topic, distinctive for its emphasis on producing quantitative conclusions. It is not in itself a specific technique, but rather an approach to aggregating information with the aid of critical deployment of standard statistical techniques. I shall discuss types of data on which met-analysis may be practised. These may be published papers or reports on past research, or the complete data on which such publications were based, whether from well-designed experiments or from other sources, or even--least satisfactorily--from spontaneously submitted information. Particular dangers are bias arising from the manner in which component studies are chosen, possibly affected by publication bias, and the pernicious influence of the modern tendency to deify the statistical significance test. A further important issue is that of the scale to be used as a measure of the effect of the treatment (or treatments) under study. I end with general comments on the conduct of met-analyses.
D J
DJ
Finney
D015982:Bias; D003627:Data Interpretation, Statistical; D015201:Meta-Analysis as Topic; D015203:Reproducibility of Results; D009626:Terminology as Topic