normTable function

Create a norm table based on model for specific age

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 range 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, 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).

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

Arguments

• A: the age as single value or a vector of age values
• model: The regression model from the cnorm function
• 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
• 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

Returns

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

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
)

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

References

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

See Also

rawTable

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