plot.PA: Plot method for PA objects.

In pcaPA: Parallel Analysis for Ordinal and Numeric Data using Polychoric and Pearson Correlations with S3 Classes

Description

plot method for objects of class PA. Plots the scree plot for a "PA" object for the selected percentiles using ggplot.

Usage

## S3 method for class 'PA'
plot(x, percentiles = NULL, main = NULL, xlab = NULL, ylab = NULL,
      groupLabel = NULL, colour = TRUE, linetype = TRUE, observed = "Observed",
      percentile = "th percentile", position = "after", sep = "", ...)

Arguments

x	an object of class "PA".
percentiles	The percentiles that ought to be plotted. Defaults to those in the PA object.
main	Graph title instead of default.
xlab	Label for x axis instead of default.
ylab	Label for y axis instead of default.
groupLabel	Legend box name instead of default.
colour	Logical indicating whether to identify the observed eigenvalues and percentiles by colour.
linetype	Logical indicating whether to identify the observed eigenvalues and percentiles by linetype.
observed	Label for the observed data, default is "observed"
percentile	Graph title instead of default.
position	Position for the percentile label. "after" will position the label after the percentile number. "before" will position the label before the percentile number
sep	Character string to separate the label from the percentiles number.
...	Not used.

Value

ggplot object for plotting the scree plot.

Author(s)

Carlos A. Arias [e-mail] and Victor H. Cervantes [e-mail]

See Also

PA, print.PA, Check.PA, CountEigen.PA, coef.PA, quantile.PA

Examples

# # Run Parallel Analysis for binary data conforming to the Rasch model
# # using the polychoric C++ function
data(simRaschData)
binaryRaschPA <- PA(simRaschData, percentiles = c(0.95, 0.99), nReplicates = 200,
                    type = "binary", algorithm = "polychoric")
print(binaryRaschPA)
plot(binaryRaschPA, percentiles = 0.99, groupLabel = "") # Plots the scree-plot
                                                         # with the 99th percentile

pcaPA documentation built on May 29, 2017, 6:53 p.m.