predictNorm {cNORM} | R Documentation |
In real test scenarios, usually the results are available as raw values, for which norm scores have to be looked up. This function conducts this reverse transformation via a numerical solution: A precise norm table is generated and the closest fitting norm score for a raw score is returned.
predictNorm(raw, A, model, minNorm = NULL, maxNorm = NULL, force = FALSE, covariate = NULL)
raw |
The raw value, either single numeric or list of values |
A |
the age, either single numeric or list of values |
model |
The regression model |
minNorm |
The lower bound of the norm score range |
maxNorm |
The upper bound of the norm score range |
force |
Try to resolve missing norm scores in case of inconsistent models |
covariate |
In case, a covariate has been used, please specify the degree of the covariate / the specific value here. |
The predicted norm score for a raw score, either single value or list of results
normData <- prepareData() m <- bestModel(data = normData) # return norm value for raw value 21 for grade 2, month 9 # Use 'as.list(normData$raw)' and 'as.list(normData$group)' for raw scores # and age to calculate predicted norm values for original data. specificNormValue <- predictNorm(raw = 21, A = 2.75, model = m, minNorm = 25, maxNorm = 75)