Continuous Norming

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Documentation for package ‘cNORM’ version 3.0.4

Help Pages

bestModel Best-fitting Regression Model Based on Powers and Interactions
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 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
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