# findRMSEApowernested: Find power given a sample size in nested model comparison In semTools: Useful Tools for Structural Equation Modeling

## Description

Find the sample size that the power in rejection the samples from the alternative pair of RMSEA is just over the specified power.

## Usage

 ```1 2``` ```findRMSEApowernested(rmsea0A = NULL, rmsea0B = NULL, rmsea1A, rmsea1B = NULL, dfA, dfB, n, alpha = 0.05, group = 1) ```

## Arguments

 `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

## Author(s)

Bell Clinton

Pavel Panko (Texas Tech University; pavel.panko@ttu.edu)

Sunthud Pornprasertmanit (psunthud@gmail.com)

## References

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
 ```1 2 3``` ```findRMSEApowernested(rmsea0A = 0.06, rmsea0B = 0.05, rmsea1A = 0.08, rmsea1B = 0.05, dfA = 22, dfB = 20, n = 200, alpha = 0.05, group = 1) ```