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.
Version: 3.4.1 Depends: R (≥ 4.0.0) Imports: leaps (≥ 3.1), ggplot2 (≥ 3.5.1) Suggests: knitr, shiny, foreign, readxl, rmarkdown, testthat Published: 2025-05-11 DOI: 10.32614/CRAN.package.cNORM Author: Alexandra Lenhard [aut], Wolfgang Lenhard [cre, aut], Sebastian Gary [aut], WPS publisher [fnd] (<https://www.wpspublish.com/>) Maintainer: Wolfgang Lenhard <wolfgang.lenhard at uni-wuerzburg.de> BugReports: https://github.com/WLenhard/cNORM/issues License: AGPL-3 URL: https://www.psychometrica.de/cNorm_en.html, https://github.com/WLenhard/cNORM NeedsCompilation: no Citation: cNORM citation info Materials: README NEWS In views: Psychometrics CRAN checks: cNORM results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=cNORM to link to this page.
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