plotRMSEApowernested {semTools}

Plot power of nested model RMSEA

Description

Plot power of nested model RMSEA over a range of possible sample sizes.

Usage

plotRMSEApowernested(rmsea0A = NULL, rmsea0B = NULL, rmsea1A,
  rmsea1B = NULL, dfA, dfB, nlow, nhigh, steps = 1, 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

nlow

Lower bound of sample size

nhigh

Upper bound of sample size

steps

Step size

alpha

The alpha level

group

The number of group in calculating RMSEA

...

The additional arguments for the plot function.

Author(s)

Bell Clinton

Pavel Panko (Texas Tech University; [e-mail])

Sunthud Pornprasertmanit ([e-mail])

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

See Also

• findRMSEApowernested to find the power for a given sample size in nested model comparison based on population RMSEA

• findRMSEAsamplesizenested to find the minium sample size for a given statistical power in nested model comparison based on population RMSEA

Examples

plotRMSEApowernested(rmsea0A = 0, rmsea0B = 0, rmsea1A = 0.06,
                     rmsea1B = 0.05, dfA = 22, dfB = 20, nlow = 50,
                     nhigh = 500, steps = 1, alpha = .05, group = 1)