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 |