cNORM (version 3.3.1)

rawTable: Create a table with norm scores assigned to raw scores for a specific age based on the regression model

Description

This function is comparable to 'normTable', despite it reverses the assignment: A table with raw scores and the according norm scores for a specific age based on the regression model is generated. This way, the inverse function of the regression model is solved numerically with brute force. Please specify the range of raw values, you want to cover. With higher precision and smaller stepping, this function becomes computational intensive. In case a confidence coefficient (CI, default .9) and the reliability is specified, confidence intervals are computed for the true score estimates, including a correction for regression to the mean (Eid & Schmidt, 2012, p. 272).

Usage

rawTable(
  A,
  model,
  minRaw = NULL,
  maxRaw = NULL,
  minNorm = NULL,
  maxNorm = NULL,
  step = 1,
  monotonuous = TRUE,
  CI = 0.9,
  reliability = NULL,
  pretty = TRUE
)

Value

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

Arguments

A

the age, either single value or vector with age values

model

The regression model or a cnorm object

minRaw

The lower bound of the raw score range

maxRaw

The upper bound of the raw score range

minNorm

Clipping parameter for the lower bound of norm scores (default 25)

maxNorm

Clipping parameter for the upper bound of norm scores (default 25)

step

Stepping parameter for the raw scores (default 1)

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

pretty

Format table by collapsing intervals and rounding to meaningful precision

References

Eid, M. & Schmidt, K. (2012). Testtheorie und Testkonstruktion. Hogrefe.

See Also

normTable

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

Examples

# Generate cnorm object from example data
cnorm.elfe <- cnorm(raw = elfe$raw, group = elfe$group)
# generate a norm table for the raw value range from 0 to 28 for the time point month 7 of grade 3
table <- rawTable(3 + 7 / 12, cnorm.elfe, minRaw = 0, maxRaw = 28)

# generate several raw tables
table <- rawTable(c(2.5, 3.5, 4.5), cnorm.elfe, minRaw = 0, maxRaw = 28)

# additionally compute confidence intervals
table <- rawTable(c(2.5, 3.5, 4.5), cnorm.elfe, minRaw = 0, maxRaw = 28, CI = .9, reliability = .94)

# conventional norming, set age to arbitrary value
model <- cnorm(raw=elfe$raw)
rawTable(0, model)