Package: cNORM
Title: Continuous Norming
Version: 3.7.0
Authors@R: c(
    person("Alexandra", "Lenhard", 
           email = "lenhard@psychometrica.de",
           role = "aut",
           comment = c(ORCID = "0000-0001-8680-4381")), 
    person("Wolfgang", "Lenhard", 
           email = "wolfgang.lenhard@uni-wuerzburg.de",
           role = c("cre", "aut"), 
           comment = c(ORCID = "0000-0002-8184-6889")),
    person("Sebastian", "Gary", 
           role = "aut"),
    person("WPS", "Publisher", 
           role = "fnd",
           comment = "https://www.wpspublish.com/"))
Description: Generates continuous test norms in psychometrics and biometrics,
    and analyzes model fit. The package offers distribution-free modeling using
    Taylor polynomials, as well as parametric modeling using the beta-binomial
    distribution (for bounded accuracy tests), the Conway-Maxwell-Poisson
    distribution (for speeded tests and count data with over-, equi-, or
    under-dispersion), and the 'Sinh-Arcsinh' (SHASH) distribution. Originally
    developed for psychological and educational assessment, it is applicable to
    a wide range of mental, physical, or other test scores dependent on
    continuous or discrete explanatory variables. The package 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 supports conventional norming. It generates norm tables including
    confidence intervals and provides methods for addressing representativeness
    issues through Iterative Proportional Fitting. Based on Lenhard et al.
    (2016) <doi:10.1177/1073191116656437>, Lenhard et al. (2019)
    <doi:10.1371/journal.pone.0222279>, Lenhard and Lenhard (2021)
    <doi:10.1177/0013164420928457>, and Gary et al. (2023)
    <doi:10.1007/s00181-023-02456-0>.
License: AGPL-3
URL: https://www.psychometrica.de/cNorm_en.html,
        https://github.com/WLenhard/cNORM
BugReports: https://github.com/WLenhard/cNORM/issues
Depends: R (>= 4.0.0)
Imports: ggplot2 (>= 3.5.0), leaps (>= 3.1), grDevices, parallel,
        stats, utils
Suggests: DT, haven, foreign, knitr, markdown, numDeriv, readxl,
        rmarkdown, shiny, shinycssloaders, testthat (>= 3.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 3
Encoding: UTF-8
Language: en-US
LazyData: true
LazyDataCompression: xz
Config/roxygen2/version: 8.0.0
NeedsCompilation: no
Packaged: 2026-10-03 09:06:42 UTC; gbpa005
Author: Alexandra Lenhard [aut] (ORCID:
    <https://orcid.org/0000-0001-8680-4381>),
  Wolfgang Lenhard [cre, aut] (ORCID:
    <https://orcid.org/0000-0002-8184-6889>),
  Sebastian Gary [aut],
  WPS Publisher [fnd] (https://www.wpspublish.com/)
Maintainer: Wolfgang Lenhard <wolfgang.lenhard@uni-wuerzburg.de>
Repository: CRAN
Date/Publication: 2026-10-03 12:20:02 UTC
Built: R 4.5.2; ; 2026-10-03 14:19:52 UTC; unix
