Factorial experiments: Efficient tools for evaluation of intervention components

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Abstract

Background: An understanding of the individual and combined effects of a set of intervention components is important for moving the science of preventive medicine interventions forward. This understanding can often be achieved in an efficient and economical way via a factorial experiment, in which two or more independent variables are manipulated. The factorial experiment is a complement to the RCT; the two designs address different research questions. Purpose: To offer an introduction to factorial experiments aimed at investigators trained primarily in the RCT. Methods: The factorial experiment is compared and contrasted with other experimental designs used commonly in intervention science to highlight where each is most efficient and appropriate. Results: Several points are made: factorial experiments make very efficient use of experimental subjects when the data are properly analyzed; a factorial experiment can have excellent statistical power even if it has relatively few subjects per experimental condition; and when conducting research to select components for inclusion in a multicomponent intervention, interactions should be studied rather than avoided. Conclusions: Investigators in preventive medicine and related areas should begin considering factorial experiments alongside other approaches. Experimental designs should be chosen from a resource management perspective, which states that the best experimental design is the one that provides the greatest scientific benefit without exceeding available resources.

Original languageEnglish (US)
Pages (from-to)498-504
Number of pages7
JournalAmerican Journal of Preventive Medicine
Volume47
Issue number4
DOIs
StatePublished - 2014

All Science Journal Classification (ASJC) codes

  • Epidemiology
  • Public Health, Environmental and Occupational Health

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