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Prev Sci. 2015 Oct;16(7):950-5. doi: 10.1007/s11121-014-0542-7.

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

Author information

1
Department of Psychology and Neuroscience, Duke University, Durham, NC, 27708, USA.
2
Department of Psychology and Neuroscience, Duke University, Durham, NC, 27708, USA. rhoyle@duke.edu.
3
Center for Developmental Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.

Abstract

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.

KEYWORDS:

Graphical methods; Maximizing statistical power; Small samples

PMID:
25578307
PMCID:
PMC4500750
DOI:
10.1007/s11121-014-0542-7
[Indexed for MEDLINE]
Free PMC Article

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