Package: cNORM 3.4.0

Wolfgang Lenhard

cNORM: Continuous Norming

A comprehensive toolkit for generating continuous test norms in psychometrics and biometrics, and analyzing model fit. The package offers both distribution-free modeling using Taylor polynomials and parametric modeling using the beta-binomial distribution. Originally developed for achievement tests, it is applicable to a wide range of mental, physical, or other test scores dependent on continuous or discrete explanatory variables. The package provides several advantages: It minimizes deviations from representativeness in subsamples, interpolates between discrete levels of explanatory variables, and significantly reduces the required sample size compared to conventional norming per age group. cNORM enables graphical and analytical evaluation of model fit, accommodates a wide range of scales including those with negative and descending values, and even supports conventional norming. It generates norm tables including confidence intervals. It also includes methods for addressing representativeness issues through Iterative Proportional Fitting.

Authors:Alexandra Lenhard [aut], Wolfgang Lenhard [cre, aut], Sebastian Gary [aut], WPS publisher [fnd]

cNORM_3.4.0.tar.gz
cNORM_3.4.0.tar.gz(r-4.5-noble)cNORM_3.4.0.tar.gz(r-4.4-noble)
cNORM_3.4.0.tgz(r-4.4-emscripten)cNORM_3.4.0.tgz(r-4.3-emscripten)
cNORM.pdf |cNORM.html✨
cNORM/json (API)
NEWS

# Install 'cNORM' in R:
install.packages('cNORM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/wlenhard/cnorm/issues

Datasets:
  • CDC - BMI growth curves from age 2 to 25
  • elfe - Sentence completion test from ELFE 1-6
  • ppvt - Vocabulary development from 2.5 to 17

4.75 score 75 scripts 879 downloads 1 mentions 49 exports 29 dependencies

Last updated 18 days agofrom:3a3873a17d. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 05 2024
R-4.5-linuxOKNov 05 2024

Exports:bestModelbetaCoefficientsbuildCnormObjectcheckConsistencycnormcnorm.betabinomialcnorm.cvcNORM.GUIcomparecomputePowerscomputeWeightsderivationTablederivediagnostics.betabinomialgetGroupsgetNormCurvegetNormScoreSEmodelSummarynormTablenormTable.betabinomialplot.cnormBetaBinomialplotCnormplotDensityplotDerivativeplotNormplotNormCurvesplotPercentilesplotPercentileSeriesplotRawplotSubsetpredict.cnormBetaBinomialpredictNormpredictRawprepareDataprintSubsetrangeCheckrankByGrouprankBySlidingWindowrawTableregressionFunctionsimulateRaschstandardizesummary.cnormBetaBinomialtaylorSwiftweighted.quantileweighted.quantile.harrell.davisweighted.quantile.inflationweighted.quantile.type7weighted.rank

Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticeleapslifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr

Demonstration for Creating Continuous Norms with cNORM

Wolfgang Lenhard, Alexandra Lenhard

Rendered fromcNORM-Demo.Rmdusingknitr::rmarkdownon Nov 05 2024.

Last update: 2024-10-16
Started: 2018-11-14

Modelling Psychometric Data with Beta-Binomial Distributions

Wolfgang Lenhard & Alexandra Lenhard

Rendered fromBetaBinomial.Rmdusingknitr::rmarkdownon Nov 05 2024.

Last update: 2024-10-16
Started: 2024-08-18

Weighted Regression-Based Norming

Sebastian Gary, Wolfgang Lenhard, Alexandra Lenhard

Rendered fromWeightedRegression.Rmdusingknitr::rmarkdownon Nov 05 2024.

Last update: 2024-08-27
Started: 2022-03-28

Readme and manuals

Help Manual

Help pageTopics
Determine Regression ModelbestModel
Compute Parameters of a Beta Binomial DistributionbetaCoefficients
Build cnorm object from data and bestModel model objectbuildCnormObject
Build regression function for bestModelbuildFunction
Internal function for retrieving regression function coefficients at specific agecalcPolyInL
Internal function for retrieving regression function coefficients at specific agecalcPolyInLBase
Internal function for retrieving regression function coefficients at specific age (optimized)calcPolyInLBase2
BMI growth curves from age 2 to 25CDC
Check Monotonicity of Predicted Valuescheck_monotonicity
Check the consistency of the norm data modelcheckConsistency
Check, if NA or values <= 0 occur and issue warningcheckWeights
Continuous Normingcnorm
Fit a beta-binomial regression model for continuous normingcnorm.betabinomial
Cross-validation for Term Selection in cNORMcnorm.cv
Launcher for the graphical user interface of cNORMcNORM.GUI
Compare Two Norm Models Visuallycompare
Compute powers of the explanatory variable a as well as of the person location l (data preparation)computePowers
Weighting of cases through iterative proportional fitting (Raking)computeWeights
Create a table based on first order derivative of the regression model for specific agederivationTable
Derivative of regression modelderive
Diagnostic Information for Beta-Binomial Modeldiagnostics.betabinomial
Sentence completion test from ELFE 1-6elfe
Determine groups and group meansgetGroups
Computes the curve for a specific T valuegetNormCurve
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 identicalgetNormScoreSE
Prints the results and regression function of a cnorm modelmodelSummary
Create a norm table based on model for specific agenormTable
Calculate Cumulative Probabilities, Density, Percentiles, and Z-Scores for Beta-Binomial DistributionnormTable.betabinomial
S3 function for plotting cnorm objectsplot.cnorm
Plot cnormBetaBinomial Model with Data and Percentile Linesplot.cnormBetaBinomial
Plot cnormBetaBinomial Model with Data and Percentile Linesplot.cnormBetaBinomial2
General convenience plotting functionplotCnorm
Plot the density function per group by raw scoreplotDensity
Plot first order derivative of regression modelplotDerivative
Plot manifest and fitted norm scoresplotNorm
Plot norm curvesplotNormCurves
Plot norm curves against actual percentilesplotPercentiles
Generates a series of plots with number curves by percentile for different modelsplotPercentileSeries
Plot manifest and fitted raw scoresplotRaw
Evaluate information criteria for regression modelplotSubset
Vocabulary development from 2.5 to 17ppvt
Predict Norm Scores from Raw Scorespredict.cnormBetaBinomial
Predict Norm Scores from Raw Scorespredict.cnormBetaBinomial2
Retrieve norm value for raw score at a specific agepredictNorm
Predict raw valuespredictRaw
Prepare data for modeling in one step (convenience method)prepareData
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.prettyPrint
S3 method for printing model selection informationprint.cnorm
Print Model Selection InformationprintSubset
Check for horizontal and vertical extrapolationrangeCheck
Determine the norm scores of the participants in each subsamplerankByGroup
Determine the norm scores of the participants by sliding windowrankBySlidingWindow
Create a table with norm scores assigned to raw scores for a specific age based on the regression modelrawTable
Regression functionregressionFunction
Simulate mean per agesimMean
Simulate sd per agesimSD
Simulate raw test scores based on Rasch modelsimulateRasch
Standardize a numeric vectorstandardize
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.standardizeRakingWeights
K-fold Resampled Coefficient Estimation for Linear Regressionsubsample_lm
S3 method for printing the results and regression function of a cnorm modelsummary.cnorm
Summarize a Beta-Binomial Continuous Norming Modelsummary.cnormBetaBinomial
Summarize a Beta-Binomial Continuous Norming Modelsummary.cnormBetaBinomial2
Swiftly compute Taylor regression models for distribution free continuous normingtaylorSwift
Weighted quantile estimatorweighted.quantile
Weighted Harrell-Davis quantile estimatorweighted.quantile.harrell.davis
Weighted quantile estimator through case inflationweighted.quantile.inflation
Weighted type7 quantile estimatorweighted.quantile.type7
Weighted rank estimationweighted.rank