Sample size planning for statistical power and accuracy in parameter estimation.
This review examines recent advances in sample size planning, not only from the perspective of an individual researcher, but also with regard to the goal of developing cumulative knowledge. Psychologists have traditionally thought of sample size planning in terms of power analysis. Although we review recent advances in power analysis, our main focus is the desirability of achieving accurate parameter estimates, either instead of or in addition to obtaining sufficient power. Accuracy in parameter estimation (AIPE) has taken on increasing importance in light of recent emphasis on effect size estimation and formation of confidence intervals. The review provides an overview of the logic behind sample size planning for AIPE and summarizes recent advances in implementing this approach in designs commonly used in psychological research.
Maxwell
Scott E
SE
Department of Psychology, University of Notre Dame, Notre Dame, Indiana 46556, USA. smaxwell@nd.edu
Kelley
Ken
K
Rausch
Joseph R
JR
D016001:Confidence Intervals; D006801:Humans; D016014:Linear Models; D008960:Models, Psychological; D011584:Psychology / Q000379:methods* / Q000706:statistics & numerical data*; D012494:Sampling Studies