Package: ANOFA
Type: Package
Title: Analyses of Frequency Data
Version: 0.1.3
Date: 2023-11-17
Authors@R: c(
             person("Denis", "Cousineau", email = "denis.cousineau@uottawa.ca",
                    role = c("aut", "cre")),
             person("Louis", "Laurencelle", email = "louis.laurencelle@gmail.com",
                    role = c("ctb")),
             person("Pier-Olivier", "Caron", email = "pocaron19@gmail.com",
                    role = c("ctb"))
           )
Author: Denis Cousineau [aut, cre],
  Louis Laurencelle [ctb],
  Pier-Olivier Caron [ctb]
Maintainer: Denis Cousineau <denis.cousineau@uottawa.ca>
BugReports: https://github.com/dcousin3/ANOFA/issues/
URL: https://dcousin3.github.io/ANOFA/
Description: 
    Analyses of frequencies can be performed using an alternative test based 
    on the G statistic. The test has similar type-I error rates and power as 
    the chi-square test. However, it is based on a total statistic that can be 
    decomposed in an additive fashion into interaction effects, main effects, simple 
    effects, contrast effects, etc., mimicking precisely the logic of ANOVA. We call 
    this set of tools 'ANOFA' (Analysis of Frequency data) to highlight its 
    similarities with ANOVA. This framework also renders plots of frequencies 
    along with confidence intervals. Finally, effect sizes and planning statistical 
    power are easily done under this framework. The ANOFA is a tool that assesses 
    the significance of effects instead of the significance of parameters; as such, 
    it is more intuitive to most researchers than alternative approaches based on 
    generalized linear models. 
    See Laurencelle and Cousineau (2023) <doi:10.20982/tqmp.19.2.p173>.
License: GPL-3
Encoding: UTF-8
VignetteBuilder: knitr
LazyData: true
RoxygenNote: 7.2.3
Depends: R (>= 3.5.0)
Imports: rrapply (>= 1.2.6), superb (>= 0.95.0), Rdpack (>= 0.7),
        ggplot2 (>= 3.1.0), stats, utils
Suggests: rmarkdown, testthat, knitr
RdMacros: Rdpack
NeedsCompilation: no
Packaged: 2023-11-17 19:57:14 UTC; Denis Cousineau
Repository: CRAN
Date/Publication: 2023-11-18 14:20:08 UTC
Built: R 4.6.0; ; 2026-04-28 23:05:18 UTC; unix
