getNormCurve: Computes the curve for a specific T value

In cNORM: Continuous Norming

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
)

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

Value

data.frame of the variables raw, age and norm

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)

cNORM documentation built on Nov. 4, 2024, 5:07 p.m.