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iotarelr: Iota Inter Coder Reliability for Content Analysis

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 ORCID iD [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:

Reference manual: iotarelr.pdf
Vignettes: Old_01_How_to_use_Iota1
02_estimating_cons
03_dgf
04_error_correction
05_new_rater
01_get_started

Downloads:

Package source: iotarelr_0.1.5.tar.gz
Windows binaries: r-devel: iotarelr_0.1.5.zip, r-release: iotarelr_0.1.5.zip, r-oldrel: iotarelr_0.1.5.zip
macOS binaries: r-release (arm64): iotarelr_0.1.5.tgz, r-oldrel (arm64): iotarelr_0.1.5.tgz, r-release (x86_64): iotarelr_0.1.5.tgz, r-oldrel (x86_64): iotarelr_0.1.5.tgz
Old sources: iotarelr archive

Reverse dependencies:

Reverse imports: aifeducation

Linking:

Please use the canonical form https://CRAN.R-project.org/package=iotarelr to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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