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cNORM
View on CRAN: Click
here
Download and install cNORM package within the R console
Install from CRAN:
install.packages("cNORM")
Install from Github:
library("remotes")
install_github("cran/cNORM")
Install by package version:
library("remotes")
install_version("cNORM", "3.0.4")
Attach the package and use:
library("cNORM")
Maintained by
Wolfgang Lenhard
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-11-14
Latest Update: 2023-10-08
Description:
Conventional methods for producing standard scores or percentiles
in psychometrics or biometrics are often plagued with 'jumps' or 'gaps'
(i.e., discontinuities) in norm tables and low confidence for assessing
extreme scores. The continuous norming method introduced by A. Lenhard et al.
(2016, ; 2019, ;
2021 ) estimates percentile development
(e. g. over age) and generates continuous test norm scores on the basis of
the raw data from standardization samples, without requiring assumptions
about the distribution of the raw data: Norm scores are directly established
from raw data by modeling the latter ones as a function of both percentile
scores and an explanatory variable (e.g., age). The method minimizes bias
arising from sampling and measurement error, while handling marked deviations
from normality, addressing bottom or ceiling effects and capturing almost
all of the variance in the original norm data sample. It includes procedures
for post stratification of norm samples to overcome bias in data collection
and to mitigate violations of representativeness. An online demonstration is
available via .
How to cite:
Wolfgang Lenhard (2018). cNORM: Continuous Norming. R package version 3.0.4, https://cran.r-project.org/web/packages/cNORM
Previous versions and publish date:
1.0.1 (2018-11-14 11:20), 1.1.2 (2018-12-08 08:30), 1.1.5 (2019-02-06 12:43), 1.1.8 (2019-03-15 13:23), 1.2.0 (2019-07-26 17:10), 1.2.2 (2019-09-19 12:50), 1.2.3 (2020-06-18 09:20), 1.2.4 (2020-11-16 16:00), 2.0.0 (2020-12-04 14:50), 2.0.1 (2021-01-06 02:10), 2.0.2 (2021-01-31 01:20), 2.0.3 (2021-04-10 15:50), 2.0.4 (2021-07-24 16:50), 2.1.0 (2021-08-12 11:40), 3.0.0 (2022-03-28 14:20), 3.0.1 (2022-04-11 11:42), 3.0.2 (2022-06-12 17:50), 3.0.3 (2023-05-22 17:00)
Other packages that cited cNORM R package
View cNORM citation profile
Other R packages that cNORM depends,
imports, suggests or enhances
Functions, R codes and Examples using
the cNORM R package
Some associated functions: CDC . bestModel . buildFunction . cNORM.GUI . cNORM . calcPolyInL . calcPolyInLBase . calcPolyInLBase2 . checkConsistency . checkWeights . cnorm.cv . computePowers . computeWeights . derivationTable . derive . elfe . epm . getGroups . getNormCurve . getNormScoreSE . life . modelSummary . mortality . normTable . plot.cnorm . plotCnorm . plotDensity . plotDerivative . plotNorm . plotNormCurves . plotPercentileSeries . plotPercentiles . plotRaw . plotSubset . ppvt . predictNorm . predictRaw . prepareData . prettyPrint . print.cnorm . printSubset . rangeCheck . rankByGroup . rankBySlidingWindow . rawTable . regressionFunction . simMean . simSD . simulateRasch . standardizeRakingWeights . summary.cnorm . weighted.quantile.harrell.davis . weighted.quantile.inflation . weighted.quantile . weighted.quantile.type7 . weighted.rank .
Some associated R codes: cNORM.R . data.R . modelling.R . plot.R . predict.R . preparation.R . raking.R . roots.R . s3methods.R . utilities.R . Full cNORM package functions and examples
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