normTable {cNORM}R Documentation

Create a norm table based on model for specific age

Description

This function generates a norm table for a specific age based on the regression model by assigning raw scores to norm scores. Please specify the range of norm scores, you want to cover. A T value of 25 corresponds to a percentile of .6. As a consequence, specifying a rang of T = 25 to T = 75 would cover 98.4 the population. Please be careful when extrapolating vertically (at the lower and upper end of the age specific distribution). Depending on the size of your standardization sample, extreme values with T < 20 or T > 80 might lead to inconsistent results. In case a confidence coefficient (CI) and the reliability is specified, confidence intervals are computed as well, including a correction for regression to the mean.

Usage

normTable(
  A,
  model,
  minNorm = NULL,
  maxNorm = NULL,
  minRaw = NULL,
  maxRaw = NULL,
  step = NULL,
  covariate = NULL,
  monotonuous = TRUE,
  CI = 0.9,
  reliability = NULL
)

Arguments

A

the age as single value or a vector of age values

model

The regression model or a cnorm object

minNorm

The lower bound of the norm score range

maxNorm

The upper bound of the norm score range

minRaw

clipping parameter for the lower bound of raw scores

maxRaw

clipping parameter for the upper bound of raw scores

step

Stepping parameter with lower values indicating higher precision

covariate

In case, a covariate has been used, please specify the degree of the covariate / the specific value here.

monotonuous

corrects for decreasing norm scores in case of model inconsistencies (default)

CI

confidence coefficient, ranging from 0 to 1, default .9

reliability

coefficient, ranging between 0 to 1

Value

either data.frame with norm scores, predicted raw scores and percentiles in case of simple A value or a list #' of norm tables if vector of A values was provided

See Also

rawTable

Other predict: derivationTable(), getNormCurve(), predictNorm(), predictRaw(), rawTable()

Examples

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

# create single norm table
norms <- normTable(3.5, cnorm.elfe, minNorm = 25, maxNorm = 75, step = 0.5)

# create list of norm tables
norms <- normTable(c(2.5, 3.5, 4.5), cnorm.elfe,
  minNorm = 25, maxNorm = 75,
  step = 1, minRaw = 0, maxRaw = 26
)

[Package cNORM version 2.0.3 Index]