predict.cnormShash: Predict Norm Scores from Raw Scores

In cNORM: Continuous Norming

Predict Norm Scores from Raw Scores

Description

This function calculates norm scores based on raw scores, age, and a fitted cnormShash model.

Usage

## S3 method for class 'cnormShash'
predict(object, ...)

Arguments

object	A fitted model object of class 'cnormShash'.
...	Additional arguments passed to the prediction method: age A numeric vector of ages, same length as score. score A numeric vector of raw scores. range The range of the norm scores in standard deviations. Default is 3. Thus, scores in the range of +/- 3 standard deviations are considered.

Details

The function predicts the Sinh-Arcsinh (shash) distribution parameters (mu, sigma, epsilon, delta) for each age using the provided model. It then calculates the cumulative probability for each raw score given these parameters using the continuous shash distribution. Finally, it converts these probabilities to the norm scale specified in the model. Raw scores at the extreme floor or ceiling of the distribution are mapped to the boundary of the norm score range (mean +/- range standard deviations), not to the mean.

Value

A numeric vector of norm scores.

See Also

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

Examples

## Not run: 
# Assuming you have a fitted model named 'shash_model':
model <- cnorm.shash(children$age, children$score)
raw_scores <- c(25.5, 30.2, 18.7, 45.3)
ages <- c(7, 8, 9, 10)
norm_scores <- predict(model, ages, raw_scores)

## End(Not run)

cNORM documentation built on July 20, 2026, 5:07 p.m.