Routines and tools for assessing the quality of content analysis on the basis of the Iota Reliability Concept. The concept is inspired by item response theory and can be applied to any kind of content analysis which uses a standardized coding scheme and discrete categories. It is also applicable for content analysis conducted by artificial intelligence. The package provides reliability measures for a complete scale as well as for every single category. Analysis of subgroup-invariance and error corrections are implemented. This information can support the development process of a coding scheme and allows a detailed inspection of the quality of the generated data. Equations and formulas working in this package are part of Berding et al. (2022)<doi:10.3389/feduc.2022.818365> and Berding and Pargmann (2022) <doi:10.30819/5581>.
Version: 0.1.5 Depends: R (≥ 3.5.0) Imports: ggplot2, ggalluvial, gridExtra, methods, Rcpp, rlang, stats LinkingTo: Rcpp Suggests: knitr, rmarkdown, testthat (≥ 3.0.0) Published: 2024-01-25 DOI: 10.32614/CRAN.package.iotarelr Author: Berding Florian [aut, cre], Pargmann Julia [ctb] Maintainer: Berding Florian <florian.berding at uni-hamburg.de> BugReports: https://github.com/FBerding/iotarelr/issues License: GPL-3 URL: https://fberding.github.io/iotarelr/ NeedsCompilation: yes Citation: iotarelr citation info Materials: README NEWS CRAN checks: iotarelr results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=iotarelr to link to this page.
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