# Continuous Norming

## Documentation for package ‘cNORM’ version 3.1.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

bestModel | Best-fitting Regression Model Based on Powers and Interactions
betaByGroup | Estimate Beta-Binomial Parameters by Group
betaCoefficients | Compute Parameters of a Beta Binomial Distribution
betaContinuous | Continuous Norming with Beta-Binomial Distribution (experimental)
betaNormTable | Generate norm table from parametric continuous norming with Beta-Binomial Parameters
betaTable | Calculate Cumulative Probabilities, Density, Percentiles, and Z-Scores for Beta-Binomial Distribution
buildFunction | Build regression function for bestModel
calcPolyInL | Internal function for retrieving regression function coefficients at specific age
calcPolyInLBase | Internal function for retrieving regression function coefficients at specific age
calcPolyInLBase2 | Internal function for retrieving regression function coefficients at specific age (optimized)
CDC | BMI growth curves from age 2 to 25
checkConsistency | Check the consistency of the norm data model
checkWeights | Check, if NA or values <= 0 occur and issue warning
cnorm | Continuous Norming
cnorm.cv | Cross-validation for Term Selection in cNORM
cNORM.GUI | Launcher for the graphical user interface of cNORM
computePowers | Compute powers of the explanatory variable a as well as of the person location l (data preparation)
computeWeights | Weighting of cases through iterative proportional fitting (Raking)
derivationTable | Create a table based on first order derivative of the regression model for specific age
derive | Derivative of regression model
elfe | Sentence completion test from ELFE 1-6
epm | Simulated dataset (Educational and Psychological Measurement, EPM)
getGroups | Determine groups and group means
getNormCurve | Computes the curve for a specific T value
getNormScoreSE | Calculates the standard error (SE) or root mean square error (RMSE) of the norm scores In case of large datasets, both results should be almost identical
life | Life expectancy at birth from 1960 to 2017
modelSummary | Prints the results and regression function of a cnorm model
mortality | Mortality of infants per 1000 life birth from 1960 to 2017
normTable | Create a norm table based on model for specific age
plot.cnorm | S3 function for plotting cnorm objects
plotCnorm | General convencience plotting function
plotDensity | Plot the density function per group by raw score
plotDerivative | Plot first order derivative of regression model
plotNorm | Plot manifest and fitted norm scores
plotNormCurves | Plot norm curves
plotPercentiles | Plot norm curves against actual percentiles
plotPercentileSeries | Generates a series of plots with number curves by percentile for different models
plotRaw | Plot manifest and fitted raw scores
plotSubset | Evaluate information criteria for regression model
ppvt | Vocabulary development from 2.5 to 17
predictBeta | Predicts beta coefficients in dependence of age
predictNorm | Retrieve norm value for raw score at a specific age
predictRaw | Predict single raw value
prepareData | Prepare data for modeling in one step (convenience method)
prettyPrint | Format raw and norm tables The function takes a raw or norm table, condenses intervals at the bottom and top and round the numbers to meaningful interval.
print.cnorm | S3 method for printing model selection information
printSubset | Print Model Selection Information
rangeCheck | Check for horizontal and vertical extrapolation
rankByGroup | Determine the norm scores of the participants in each subsample
rankBySlidingWindow | Determine the norm scores of the participants by sliding window (experimental)
rawTable | Create a table with norm scores assigned to raw scores for a specific age based on the regression model
regressionFunction | Regression function
simMean | Simulate mean per age
simSD | Simulate sd per age
simulateRasch | Simulate raw test scores based on Rasch model
standardizeRakingWeights | Function for standardizing raking weights Raking weights get divided by the smallest weight. Thereby, all weights become larger or equal to 1 without changing the ratio of the weights to each other.
summary.cnorm | S3 method for printing the results and regression function of a cnorm model
weighted.quantile | Weighted quantile estimator
weighted.quantile.harrell.davis | Weighted Harrell-Davis quantile estimator
weighted.quantile.inflation | Weighted quantile estimator through case inflation
weighted.quantile.type7 | Weighted type7 quantile estimator
weighted.rank | Weighted rank estimation