Man pages for WLenhard/cNORM
Continuous Norming
| bestModel | Determine Regression Model |
| betaCoefficients | Compute Parameters of a Beta Binomial Distribution |
| buildCnormObject | Build cnorm object from data and bestModel model object |
| buildFunction | Build regression function for bestModel |
| calcPolyInL | Internal function for retrieving regression function... |
| calcPolyInLBase | Internal function for retrieving regression function... |
| calcPolyInLBase2 | Internal function for retrieving regression function... |
| CDC | BMI growth curves from age 2 to 25 |
| checkConsistency | Check the consistency of the norm data model |
| check_monotonicity | Check Monotonicity of Predicted Values |
| checkWeights | Check, if NA or values <= 0 occur and issue warning |
| cNORM | Continuous Norming |
| cnorm.betabinomial | Fit a beta-binomial regression model for continuous norming |
| cnorm.betabinomial1 | Fit a beta binomial regression model |
| cnorm.betabinomial2 | Fit a beta-binomial regression model for continuous norming |
| cnorm.cv | Cross-validation for Term Selection in cNORM |
| cNORM.GUI | Launcher for the graphical user interface of cNORM |
| compare | Compare Two Norm Models Visually |
| computePowers | Compute powers of the explanatory variable a as well as of... |
| computeWeights | Weighting of cases through iterative proportional fitting... |
| derivationTable | Create a table based on first order derivative of the... |
| derive | Derivative of regression model |
| diagnostics.betabinomial | Diagnostic Information for Beta-Binomial Model |
| elfe | Sentence completion test from ELFE 1-6 |
| 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... |
| log_likelihood | Calculate the negative log-likelihood for a beta binomial... |
| log_likelihood2 | Calculate the negative log-likelihood for a beta-binomial... |
| modelSummary | Prints the results and regression function of a cnorm model |
| normTable | Create a norm table based on model for specific age |
| normTable.betabinomial | Calculate Cumulative Probabilities, Density, Percentiles, and... |
| plot.cnorm | S3 function for plotting cnorm objects |
| plotCnorm | General convenience plotting function |
| plot.cnormBetaBinomial | Plot cnormBetaBinomial Model with Data and Percentile Lines |
| plot.cnormBetaBinomial2 | Plot cnormBetaBinomial Model with Data and Percentile Lines |
| 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... |
| plotRaw | Plot manifest and fitted raw scores |
| plotSubset | Evaluate information criteria for regression model |
| ppvt | Vocabulary development from 2.5 to 17 |
| predict.cnormBetaBinomial | Predict Norm Scores from Raw Scores |
| predict.cnormBetaBinomial2 | Predict Norm Scores from Raw Scores |
| predictCoefficients | Predict mean and standard deviation for a beta binomial... |
| predictCoefficients2 | Predict alpha and beta parameters for a beta-binomial... |
| predictNorm | Retrieve norm value for raw score at a specific age |
| predictRaw | Predict raw values |
| prepareData | Prepare data for modeling in one step (convenience method) |
| prettyPrint | Format raw and norm tables The function takes a raw or norm... |
| 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... |
| rankBySlidingWindow | Determine the norm scores of the participants by sliding... |
| rawTable | Create a table with norm scores assigned to raw scores for a... |
| regressionFunction | Regression function |
| simMean | Simulate mean per age |
| simSD | Simulate sd per age |
| simulateRasch | Simulate raw test scores based on Rasch model |
| standardize | Standardize a numeric vector |
| standardizeRakingWeights | Function for standardizing raking weights Raking weights get... |
| subsample_lm | K-fold Resampled Coefficient Estimation for Linear Regression |
| summary.cnorm | S3 method for printing the results and regression function of... |
| summary.cnormBetaBinomial | Summarize a Beta-Binomial Continuous Norming Model |
| summary.cnormBetaBinomial2 | Summarize a Beta-Binomial Continuous Norming Model |
| taylorSwift | Swiftly compute Taylor regression models for distribution... |
| 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 |
