cNORM (version 3.3.1)

getNormCurve: Computes the curve for a specific T value

Description

As with this continuous norming regression approach, raw scores are modeled as a function of age and norm score (location), getNormCurve is a straightforward approach to show the raw score development over age, while keeping the norm value constant. This way, e. g. academic performance or intelligence development of a specific ability is shown.

Usage

getNormCurve(
  norm,
  model,
  minAge = NULL,
  maxAge = NULL,
  step = 0.1,
  minRaw = NULL,
  maxRaw = NULL
)

Value

data.frame of the variables raw, age and norm

Arguments

norm

The specific norm score, e. g. T value

model

The model from the regression modeling obtained with the cnorm function

minAge

Age to start from

maxAge

Age to stop at

step

Stepping parameter for the precision when retrieving of the values, lower values indicate higher precision (default 0.1).

minRaw

lower bound of the range of raw scores (default = 0)

maxRaw

upper bound of raw scores

See Also

Other predict: derivationTable(), normTable(), predict.cnormBetaBinomial(), predict.cnormBetaBinomial2(), predictNorm(), predictRaw(), rawTable()

Examples

# Generate cnorm object from example data
cnorm.elfe <- cnorm(raw = elfe$raw, group = elfe$group)
getNormCurve(35, cnorm.elfe)