Meta-Analysis for Medical Decisions

28 Pages Posted: 4 Feb 2019

See all articles by Charles F. Manski

Charles F. Manski

Northwestern University - Department of Economics; National Bureau of Economic Research (NBER)

Date Written: January 2019

Abstract

Statisticians have proposed meta-analysis to combine the findings of multiple studies of health risks or treatment response. The standard practice is to compute a weighted-average of the estimates. Yet it is not clear how to interpret a weighted average of estimates reported in disparate studies. Meta-analyses often answer this question through the lens of a random-effects model, which interprets a weighted average of estimates as an estimate of a mean parameter across a hypothetical population of studies. The relevance to medical decision making is obscure. Decision-centered research should aim to inform risk assessment and treatment for populations of patients, not populations of studies. This paper lays out principles for decision-centered meta-analysis. One first specifies a prediction of interest and next examines what each available study credibly reveals. Such analysis typically yields a set-valued prediction rather than a point prediction. Thus, one uses each study to conclude that a probability of disease, or mean treatment response, lies within a range of possibilities. Finally, one combines the available studies by computing the intersection of the set-valued predictions that they yield. To demonstrate decision-centered meta-analysis, the paper considers assessment of the effect of anti-hypertensive drugs on blood pressure.

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Suggested Citation

Manski, Charles F., Meta-Analysis for Medical Decisions (January 2019). NBER Working Paper No. w25504, Available at SSRN: https://ssrn.com/abstract=3328327

Charles F. Manski (Contact Author)

Northwestern University - Department of Economics ( email )

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