Factorial experiments: efficient tools for evaluation of intervention components

Am J Prev Med. 2014 Oct;47(4):498-504. doi: 10.1016/j.amepre.2014.06.021. Epub 2014 Aug 1.


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.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Humans
  • Preventive Health Services / methods*
  • Preventive Medicine / methods
  • Randomized Controlled Trials as Topic / methods*
  • Research Design*