simsem (version 0.2-8)

plotPowerFitDf: Plot sampling distributions of fit indices that visualize power of rejecting datasets underlying misspecified models

Description

This function will plot sampling distributions of fit indices that visualize power in rejecting the misspecified models. This function is similar to the plotPowerFit function but the input distributions are data.frame.

Usage

plotPowerFitDf(altObject, nullObject = NULL, cutoff = NULL, usedFit = NULL, alpha = 0.05, x = NULL, xval = NULL, useContour = TRUE, logistic = TRUE)

Arguments

altObject

The result object (data.frame) saves the simulation result of fitting the hypothesized model when the hypothesized model is FALSE.

nullObject

The result object (data.frame) saves the simulation result of fitting the hypothesized model when the hypothesized model is TRUE. This argument may be not specified if the cutoff is specified.

cutoff

A vector of priori cutoffs for fit indices.

usedFit

Vector of names of fit indices that researchers wish to plot.

alpha

A priori alpha level

x

The data.frame of the predictor values. The number of rows of the x argument should be equal to the number of rows in the object.

xval

The values of predictor that researchers would like to find the fit indices cutoffs from.

useContour

If there are two of sample size, percent completely at random, and percent missing at random are varying, the plotCutoff function will provide 3D graph. Contour graph is a default. However, if this is specified as FALSE, perspect

logistic

If logistic is TRUE and the varying parameter exists (e.g., sample size or percent missing), the plot based on logistic regression predicting the significance by the varying parameters is preferred. If FALSE, the ove

Value

• NONE. Only plot the fit indices distributions.

See Also

• plotPowerFit

Examples

# No example