Description Usage Arguments Details Author(s) References See Also Examples
View source: R/powerAnalysisRMSEA.R
Find the proportion of the samples from the sampling distribution of RMSEA in the alternative hypothesis rejected by the cutoff dervied from the sampling distribution of RMSEA in the null hypothesis. This function can be applied for both test of close fit and test of notclose fit (MacCallum, Browne, & Suguwara, 1996)
1  findRMSEApower(rmsea0, rmseaA, df, n, alpha = 0.05, group = 1)

rmsea0 
Null RMSEA 
rmseaA 
Alternative RMSEA 
df 
Model degrees of freedom 
n 
Sample size of a dataset 
alpha 
Alpha level used in power calculations 
group 
The number of group that is used to calculate RMSEA. 
This function find the proportion of sampling distribution derived from the
alternative RMSEA that is in the critical region derived from the sampling
distribution of the null RMSEA. If rmseaA
is greater than
rmsea0
, the test of close fit is used and the critical region is in
the right hand side of the null sampling distribution. On the other hand, if
rmseaA
is less than rmsea0
, the test of notclose fit is used
and the critical region is in the left hand side of the null sampling
distribution (MacCallum, Browne, & Suguwara, 1996).
Sunthud Pornprasertmanit (psunthud@gmail.com)
MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1(2), 130–149. doi: 10.1037/1082989X.1.2.130
plotRMSEApower
to plot the statistical power based on
population RMSEA given the sample size
plotRMSEAdist
to visualize the RMSEA distributions
findRMSEAsamplesize
to find the minium sample size for
a given statistical power based on population RMSEA
1  findRMSEApower(rmsea0 = .05, rmseaA = .08, df = 20, n = 200)

Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.