Iota Inter Coder Reliability for Content Analysis
Check assumptions of weak superiority
Check for Different Guidance Functioning (DGF)
Check new rater
Computes Iota and its elements in version 1
Computes Iota and its elements in version 2
Parameter estimation via EM Algorithm with Condition Stage
Estimating log likelihood in Condition Stage
Estimate Expected Categories
Estimating log-likelihood
Get Consequences
Get Iota2 Measures
Get patterns
Generating randomly chosen probabilities for categorical sizes
Generating randomly chosen probabilities for Assignment Error Matrix
Get Summary
Gradient for Log Likelihood in Condition Stage
Estimating log-likelihood in Condition Stage
Plot Iota2
Plot of the Coding Stream
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>.