plotPercentileSeries function

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

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.

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

Arguments

• model: The Taylor polynomial regression model object from the cNORM
• 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)
• filename: Prefix of the filename. If specified, the plots are saves as png files in the directory of the workspace, instead of displaying them

Returns

the complete list of plots

Examples

# Load example data set, compute model and plot results
result <- cnorm(raw = elfe$raw, group = elfe$group)
plotPercentileSeries(result, start=4, end=6)

See Also

plotPercentiles

Other plot: compare(), plot.cnorm(), plot.cnormBetaBinomial(), plot.cnormBetaBinomial2(), plotDensity(), plotDerivative(), plotNorm(), plotNormCurves(), plotPercentiles(), plotRaw(), plotSubset()