Integration of Evidence Across Studies
Multiple studies provide an opportunity to evaluate patterns of results to draw firmer conclusions. A series of studies yielding inconsistent results may well provide strong support for a causal inference when the methodologic features of those studies are scrutinized and the subset of studies that support an association are methodologically stronger, while those that fail to find an association are weaker. Similarly, consistent evidence of an association may not support a causal relation if all the studies share the same bias that is likely to generate spurious indications of a positive association. In order to draw conclusions, the methods and results must be considered in relation to one another, both within and across studies. This chapter discusses the consideration of random error and bias, data pooling and coordinated comparative analysis, synthetic and exploratory meta-analysis, interpreting consistency and inconsistency, and integrated assessment from combining evidence across studies.
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