plotPower: Plot sampling distributions of fit indices that visualize power

Description

This function will plot sampling distributions of fit indices that visualize power in either a histogram or overlapping histograms.

Usage

plotPower(altObject, nullObject, ...)

Arguments

altObject

The object (SimResult or data.frame) that saves fit indices for alternative hypothesis

nullObject

The object that represents null hypothesis. It can be vector of cutoffs (that might be calculated from getCutoff or an object that save raw data of fit indices for null hypothesis (<

...

Other arguments specific to different types of object you pass in the function.

Value

NONE. Only plot the fit indices distributions.

Details in ...

alpha: A priori alpha level to getCutoffs of fit indices (do not specify when you havecutoff)
usedFit: The name of fit indices that researchers wish to plot

Examples

Run this code

loading.null <- matrix(0, 6, 1)
loading.null[1:6, 1] <- NA
LX.NULL <- simMatrix(loading.null, 0.7)
RPH.NULL <- symMatrix(diag(1))
RTD <- symMatrix(diag(6))
CFA.Model.NULL <- simSetCFA(LY = LX.NULL, RPS = RPH.NULL, RTE = RTD)
SimData.NULL <- simData(CFA.Model.NULL, 500)
SimModel <- simModel(CFA.Model.NULL)
# We make the examples running only 5 replications to save time.
# In reality, more replications are needed.
Output.NULL <- simResult(5, SimData.NULL, SimModel)
Cut.NULL <- getCutoff(Output.NULL, 0.95)

u79 <- simUnif(0.7, 0.9)
loading.alt <- matrix(0, 6, 2)
loading.alt[1:3, 1] <- NA
loading.alt[4:6, 2] <- NA
LX.ALT <- simMatrix(loading.alt, 0.7)
latent.cor.alt <- matrix(NA, 2, 2)
diag(latent.cor.alt) <- 1
RPH.ALT <- symMatrix(latent.cor.alt, "u79")
CFA.Model.ALT <- simSetCFA(LY = LX.ALT, RPS = RPH.ALT, RTE = RTD)
SimData.ALT <- simData(CFA.Model.ALT, 500)
Output.ALT <- simResult(5, SimData.ALT, SimModel)
getPower(Output.ALT, Cut.NULL)
Rule.of.thumb <- c(RMSEA=0.05, CFI=0.95, TLI=0.95, SRMR=0.06)
plotPower(Output.ALT, Output.NULL, alpha=0.05, usedFit=c("RMSEA", "CFI", "TLI", "SRMR"))