Chapter

Integration of Evidence Across Studies

David A. Savitz

in Interpreting Epidemiologic Evidence

Published in print July 2003 | ISBN: 9780195108408
Published online September 2009 | e-ISBN: 9780199865765 | DOI: http://dx.doi.org/10.1093/acprof:oso/9780195108408.003.0011
Integration of Evidence Across Studies

More Like This

Show all results sharing this subject:

  • Public Health and Epidemiology

GO

Show Summary Details

Preview

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.

Keywords: epidemiological research; epidemiological studies; random error; bias; data pooling; comparative analysis; integrated assessment; consistency

Chapter.  10015 words.  Illustrated.

Subjects: Public Health and Epidemiology

Full text: subscription required

How to subscribe Recommend to my Librarian

Buy this work at Oxford University Press »

Users without a subscription are not able to see the full content. Please, subscribe or login to access all content.