cNORM (version 3.0.3)

plotPercentileSeries: 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
)

Value

the complete list of plots

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

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")