(Sample) Size Matters

Sample Size Matters

On this blog and others, on twitter (@mwkraus), at conferences, and in the halls of the psychology building at the University of Illinois, I have engaged in a wealth of important discussions about improving research methods in social-personality psychology. Many prominent psychologists have offered several helpful suggestions in this regard (here, here, here, and here).

Among the many suggestions for building a better psychological science, perhaps the simplest and most parsimonious way to improve research methods is to increase sample sizes for all study designs: By increasing sample size researchers can detect smaller real effects and can more accurately measure large effects. There are many trade-offs in choosing appropriate research methods, but sample size, at least for a researcher like me who deals in relatively inexpensive data collection tools, is in many ways the most cost effective way to improve one's science. In essence, I can continue to design the studies I have been designing and ask the same research questions I have been asking (i.e., business-as-usual) with the one exception that each study I run has a larger N than it would have if I were not thinking (more) intelligently about statistical power.

How has my lab been fairing with respect to this goal of collecting large samples? See for yourself:

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