View source: R/powerAnalysisNested.R
findRMSEApowernested | R Documentation |
Find the sample size that the power in rejection the samples from the alternative pair of RMSEA is just over the specified power.
findRMSEApowernested(rmsea0A = NULL, rmsea0B = NULL, rmsea1A, rmsea1B = NULL, dfA, dfB, n, alpha = 0.05, group = 1)
rmsea0A |
The H_0 baseline RMSEA |
rmsea0B |
The H_0 alternative RMSEA (trivial misfit) |
rmsea1A |
The H_1 baseline RMSEA |
rmsea1B |
The H_1 alternative RMSEA (target misfit to be rejected) |
dfA |
degree of freedom of the more-restricted model |
dfB |
degree of freedom of the less-restricted model |
n |
Sample size |
alpha |
The alpha level |
group |
The number of group in calculating RMSEA |
Bell Clinton
Pavel Panko (Texas Tech University; pavel.panko@ttu.edu)
Sunthud Pornprasertmanit (psunthud@gmail.com)
MacCallum, R. C., Browne, M. W., & Cai, L. (2006). Testing differences between nested covariance structure models: Power analysis and null hypotheses. Psychological Methods, 11(1), 19–35. doi: 10.1037/1082-989X.11.1.19
plotRMSEApowernested
to plot the statistical power for
nested model comparison based on population RMSEA given the sample size
findRMSEAsamplesizenested
to find the minium sample
size for a given statistical power in nested model comparison based on
population RMSEA
findRMSEApowernested(rmsea0A = 0.06, rmsea0B = 0.05, rmsea1A = 0.08, rmsea1B = 0.05, dfA = 22, dfB = 20, n = 200, alpha = 0.05, group = 1)
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