Abstract

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.

Keywords

Sample size determinationSample (material)Perspective (graphical)EstimationStatistical powerPsychologyComputer sciencePower (physics)Management scienceStatisticsArtificial intelligenceMathematicsEngineeringSystems engineering

MeSH Terms

Confidence IntervalsHumansLinear ModelsModelsPsychologicalPsychologySampling Studies

Affiliated Institutions

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Publication Info

Year
2007
Type
review
Volume
59
Issue
1
Pages
537-563
Citations
523
Access
Closed

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Cite This

Scott E. Maxwell, Ken Kelley, Joseph R. Rausch (2007). Sample Size Planning for Statistical Power and Accuracy in Parameter Estimation. Annual Review of Psychology , 59 (1) , 537-563. https://doi.org/10.1146/annurev.psych.59.103006.093735

Identifiers

DOI
10.1146/annurev.psych.59.103006.093735
PMID
17937603

Data Quality

Data completeness: 81%