doi:10.1177/25152459241293110>, users upload the research variables and the app guides them to the best set of comparisons fitting the hypotheses, for both main and interaction effects. Through a graphical explanation and empirical examples on reproducible data, it is shown that it is possible to understand both the logic behind the planned comparisons and the way to interpret them when a model is tested.">

appRiori: Code and Obtain Customized Planned Comparisons with 'appRiori' (original) (raw)

With 'appRiori' <doi:10.1177/25152459241293110>, users upload the research variables and the app guides them to the best set of comparisons fitting the hypotheses, for both main and interaction effects. Through a graphical explanation and empirical examples on reproducible data, it is shown that it is possible to understand both the logic behind the planned comparisons and the way to interpret them when a model is tested.

Version: 0.0.6
Imports: dplyr, DT, hypr, markdown, MASS, pracma, rhandsontable, shiny, shinythemes, sortable, stringr
Published: 2025-02-27
DOI: 10.32614/CRAN.package.appRiori
Author: Umberto Granziol [aut, cre], Maximilian Rabe ORCID iD [aut], Andrea Spoto [aut], Giulio Vidotto [aut], Marcello Gallucci [aut]
Maintainer: Umberto Granziol <umberto.granziol at unipd.it>
BugReports: https://github.com/Ugranziol/appRiori/issues
License: GPL (≥ 3)
URL: https://github.com/Ugranziol/appRiori
NeedsCompilation: no
Citation: appRiori citation info
CRAN checks: appRiori results

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