Literature DB >> 322841

Epidemiologic methods in clinical trials.

K J Rothman.   

Abstract

Epidemiologic methods developed to control confounding in non-experimental studies are equally applicable for experiments. In experiments, most confounding is usually controlled by random allocation of subjects to treatment groups, but randomization does not preclude confounding except for extremely large studies, the degree of confounding expected being inversely related to the size of the treatment groups. In experiments, as in non-experimental studies, the extent of confounding for each risk indicator should be assessed, and if sufficiently large, controlled. Confounding is properly assessed by comparing the unconfounded effect estimate to the crude effect estimate; a common error is to assess confounding by statistical tests of significance. Assessment of confounding involves its control as a prerequisite. Control is most readily and cogently achieved by stratification of the data, though with many factors to control simultaneously, multivariate analysis or a combination of multivariate analysis and stratification might be necessary.

Mesh:

Year:  1977        PMID: 322841     DOI: 10.1002/1097-0142(197704)39:4+<1771::aid-cncr2820390803>3.0.co;2-2

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


  18 in total

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Authors:  Uyen-Sa D T Nguyen; Kenneth J Rothman; Serkalem Demissie; Debra J Jackson; Janet M Lang; Jeffrey L Ecker
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6.  Limitations of individual causal models, causal graphs, and ignorability assumptions, as illustrated by random confounding and design unfaithfulness.

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8.  Modeling and variable selection in epidemiologic analysis.

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9.  A fair trial?

Authors:  D G Altman
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10.  Identifiability, exchangeability and confounding revisited.

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