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In order to check model assumptions, a table of the first order derivative of the model coefficients is created.
derivationTable(A, model, minNorm = NULL, maxNorm = NULL, step = 0.1)
data.frame with norm scores and the predicted scores based on the derived regression function
the age
The regression model or a cnorm object
The lower bound of the norm value range
The upper bound of the norm value range
Stepping parameter with lower values indicating higher precision
plotDerivative, derive
Other predict: getNormCurve(), normTable(), predict.cnormBetaBinomial(), predict.cnormBetaBinomial2(), predictNorm(), predictRaw(), rawTable()
getNormCurve()
normTable()
predict.cnormBetaBinomial()
predict.cnormBetaBinomial2()
predictNorm()
predictRaw()
rawTable()
# Generate cnorm object from example data cnorm.elfe <- cnorm(raw = elfe$raw, group = elfe$group) # retrieve function for time point 6 d <- derivationTable(6, cnorm.elfe, step = 0.5)
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