Abstract
Abstract A common question asked by researchers is, "What sample size do I need for my study?" Over the years, several rules of thumb have been proposed. In reality there is no rule of thumb that applies to all situations. The sample size needed for a study depends on many factors, including the size of the model, distribution of the variables, amount of missing data, reliability of the variables, and strength of the relations among the variables. The purpose of this article is to demonstrate how substantive researchers can use a Monte Carlo study to decide on sample size and determine power. Two models are used as examples, a confirmatory factor analysis (CFA) model and a growth model. The analyses are carried out using the Mplus program (Muthén& Muthén 1998).
Keywords
Sample size determinationRule of thumbMonte Carlo methodSample (material)EconometricsStatisticsConfirmatory factor analysisStructural equation modelingReliability (semiconductor)PsychologyComputer sciencePower (physics)MathematicsAlgorithm
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Publication Info
- Year
- 2002
- Type
- article
- Volume
- 9
- Issue
- 4
- Pages
- 599-620
- Citations
- 2142
- Access
- Closed
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Cite This
Linda K. Muthén,
Bengt Muthén
(2002).
How to Use a Monte Carlo Study to Decide on Sample Size and Determine Power.
Structural Equation Modeling A Multidisciplinary Journal
, 9
(4)
, 599-620.
https://doi.org/10.1207/s15328007sem0904_8
Identifiers
- DOI
- 10.1207/s15328007sem0904_8