plotPercentileSeries: Generates a series of plots with number curves by percentile...

In WLenhard/cNORM: Continuous Norming

Generates a series of plots with number curves by percentile for different models

Description

This functions makes use of 'plotPercentiles' to generate a series of plots with different number of predictors. It draws on the information provided by the model object to determine the bounds of the modeling (age and standard score range). It can be used as an additional model check to determine the best fitting model. Please have a look at the ' plotPercentiles' function for further information.

Usage

plotPercentileSeries(
  data,
  model,
  start = 1,
  end = NULL,
  group = NULL,
  percentiles = c(0.025, 0.1, 0.25, 0.5, 0.75, 0.9, 0.975),
  type = 7,
  filename = NULL
)

Arguments

data	The raw data including the percentiles and norm scores or a cnorm object
model	The model from the bestModel function (optional)
start	Number of predictors to start with
end	Number of predictors to end with
group	The name of the grouping variable; the distinct groups are automatically determined
percentiles	Vector with percentile scores, ranging from 0 to 1 (exclusive)
type	The type parameter of the quantile function to estimate the percentiles of the raw data (default 7)
filename	Prefix of the filename. If specified, the plots are saves as png files in the directory of the workspace, instead of displaying them

Value

the complete list of plots

See Also

plotPercentiles

Other plot: plot.cnorm(), plotDensity(), plotDerivative(), plotNormCurves(), plotNorm(), plotPercentiles(), plotRaw(), plotSubset()

Examples

# Load example data set, compute model and plot results
result <- cnorm(raw = elfe$raw, group = elfe$group)
plotPercentileSeries(result, start=1, end=5, group="group")

WLenhard/cNORM documentation built on April 1, 2024, 5:41 p.m.