Prevention Science

, Volume 16, Issue 7, pp 950–955 | Cite as

Maximizing the Yield of Small Samples in Prevention Research: A Review of General Strategies and Best Practices

  • Cameron R. Hopkin
  • Rick H. HoyleEmail author
  • Nisha C. Gottfredson


The goal of this manuscript is to describe strategies for maximizing the yield of data from small samples in prevention research. We begin by discussing what “small” means as a description of sample size in prevention research. We then present a series of practical strategies for getting the most out of data when sample size is small and constrained. Our focus is the prototypic between-group test for intervention effects; however, we touch on the circumstance in which intervention effects are qualified by one or more moderators. We conclude by highlighting the potential usefulness of graphical methods when sample size is too small for inferential statistical methods.


Small samples Maximizing statistical power Graphical methods 



During the writing of this manuscript, the authors were supported by National Institute on Drug Abuse (NIDA) Grant P30 DA023026. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of NIDA.

Conflict of Interest

The authors declare that they have no conflict of interest.


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Copyright information

© Society for Prevention Research 2015

Authors and Affiliations

  • Cameron R. Hopkin
    • 1
  • Rick H. Hoyle
    • 1
    Email author
  • Nisha C. Gottfredson
    • 2
  1. 1.Department of Psychology and NeuroscienceDuke UniversityDurhamUSA
  2. 2.Center for Developmental Science, University of North Carolina at Chapel HillChapel HillUSA

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