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semTools (version 0.5-0)

plotRMSEApowernested: 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.

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

Run this code
# NOT RUN {
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)

# }

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