EFAtools (version 1.1.0)

plot.efa_power: Plot the RMSEA power curve

Description

Draws the analytic RMSEA power (MacCallum, Browne, & Sugawara, 1996) of an efa_power() result as a function of the total sample size, mirroring semTools::plotRMSEApower() but returning a ggplot2::ggplot object rather than drawing to the active device. The test, its null and alternative RMSEA, the significance level, and the number of groups are taken from the object; only the sample-size axis is swept, with an optional sweep of the degrees of freedom or the alternative RMSEA to overlay several curves.

Usage

# S3 method for efa_power
plot(x, n = NULL, df = NULL, eps1 = NULL, ...)

Value

A ggplot2::ggplot object.

Arguments

x

An object of class efa_power (output from efa_power()).

n

numeric. The total sample sizes to evaluate. If NULL (the default) a sequence bracketing the object's sample size is chosen automatically.

df

numeric. The model degrees of freedom (must be positive). Defaults to the object's df; a vector of length greater than one draws one curve per value.

eps1

numeric. The alternative-hypothesis RMSEA (must differ from the null eps0). Defaults to the object's eps1; a vector of length greater than one draws one curve per value. At most one of df and eps1 may be a vector.

...

Not used; for consistency with the generic.

Details

When the plotted curve is the object's own -- a single curve with neither df nor eps1 overridden -- it is annotated with the object's result: a dashed vertical line at its sample size x$N, a dashed horizontal line at the reference power (the target power when a sample size was solved for, otherwise the power achieved at x$N), and a point at x$N and the achieved power. Overriding df or eps1, sweeping either as a vector, or supplying an n that does not span x$N moves that point off the drawn curve, so the marks are then omitted.

References

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. tools:::Rd_expr_doi("10.1037/1082-989X.1.2.130")

See Also

Other power analysis: efa_power(), print.efa_power()

Examples

pw <- efa_power(df = 100, N = 200)

# Power curve for the test of close fit, marking the object's own N
plot(pw)

# Overlay several models by sweeping the degrees of freedom
plot(pw, df = c(50, 100, 200))

# Sweep the alternative RMSEA instead
plot(pw, eps1 = c(0.06, 0.08, 0.10))