R: Computing the Extent of Agreement among Raters with Chance-Corrected Agreement Coefficient (CAC)

# Computing the Extent of Agreement among Raters with Chance-Corrected Agreement Coefficient (CAC)

## Documentation for package ‘irrCAC’ version 1.4

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

agree.cac3rd | Dataset showing the distribution of 6 raters by psychiatric condition
agree.contingency | Dataset representing a 10x10 contingency table
agreeCAC | Ratings of 15 subjects from 4 raters
altman | Dataset describing the Altman's Benchmarking Scale
altman.bf | Computing Altman's Benchmark Scale Membership Probabilities
bangdiwala.table | Bangdiwala B coefficient for 2 raters
bangdiwala2RR.fn | Bangdiwala B coefficient for 2 raters when input dataset is made up of 2 columns of raw data.
bipolar.weights | Function for computing the Bipolar Weights
bp.coeff.dist | Brennan-Prediger's agreement coefficient among multiple raters (2, 3, +) when the input dataset is the distribution of raters by subject and category.
bp.coeff.raw | Brennan & Prediger's (BP) agreement coefficient for an arbitrary number of raters (2, 3, +) when the input data represent the raw ratings reported for each subject and each rater.
bp2.table | Brenann-Prediger coefficient for 2 raters
cac.ben.gerry | Ratings of 12 units from 2 raters named Ben and Gerry
cac.dist.g1g2 | Distribution of 4 raters by subject and by category, for 14 Subjects that belong to 2 groups "G1" and "G2"
cac.dist4cat | Distribution of 4 raters by Category and Subject - Subjects allocated in 2 groups A and B.
cac.raw.g1g2 | Dataset of raw ratings from 4 Raters on 14 Subjects that belong to 2 groups named "G1" and "G2"
cac.raw.gender | Rating Data from 4 Raters and 15 human Subjects, 9 of whom are female and 6 males.
cac.raw2raters | Dataset of raw ratings by 2 raters and 12 subjects.
cac.raw4raters | Rating Data from 4 Raters and 12 Subjects.
cac.raw5obser | Scores assigned by 5 observers to 20 experimental units.
circular.weights | Function for computing the Circular Weights
conger.kappa.raw | Conger's generalized kappa coefficient for an arbitrary number of raters (2, 3, +) when the input data represent the raw ratings reported for each subject and each rater.
cont3x3abstractors | Distribution of 100 pregnant women by pregnancy type and by abstractor.
cont4x4diagnosis | Distribution of 223 Psychiatric Patients by Type of of Psychiatric Disorder and Diagnosis Method.
distrib.6raters | Distribution of 6 psychiatrists by Subject/patient and diagnosis Category.
fleiss | Dataset describing Fleiss' Benchmarking Scale
fleiss.bf | Computing Fleiss Benchmark Scale Membership Probabilities
fleiss.kappa.dist | Fleiss' agreement coefficient among multiple raters (2, 3, +) when the input dataset is the distribution of raters by subject and category.
fleiss.kappa.raw | Fleiss' generalized kappa among multiple raters (2, 3, +) when the input data represent the raw ratings reported for each subject and each rater.
freq.supp.fn | freq.supp.fn: This function reads a 3-variable input data file containing unique pairs of categories along with their frequency of occurrences, and outputs a similar file where all possible pairs of categories are represented, some with a frequency of occurrence of 0.
freqs.data | Distribution of 10 subjects by rater (Ben and Gerry) and by category.
gwet.ac1.dist | Gwet's AC1/AC2 agreement coefficient among multiple raters (2, 3, +) when the input dataset is the distribution of raters by subject and category.
gwet.ac1.raw | Gwet's AC1/AC2 agreement coefficient among multiple raters (2, 3, +) when the input data represent the raw ratings reported for each subject and each rater.
gwet.ac1.table | Gwet's AC1/AC2 coefficient for 2 raters
identity.weights | Function for computing the Identity Weights
kappa2.table | Kappa coefficient for 2 raters
krippen.alpha.dist | Krippendorff's agreement coefficient among multiple raters (2, 3, +) when the input dataset is the distribution of raters by subject and category.
krippen.alpha.raw | Krippendorff's alpha coefficient for an arbitrary number of raters (2, 3, +) when the input data represent the raw ratings reported for each subject and each rater.
krippen2.table | Krippendorff's Alpha coefficient for 2 raters
landis.koch | Dataset describing the Landis & Koch Benchmarking Scale
landis.koch.bf | Computing Landis-Koch Benchmark Scale Membership Probabilities
linear.weights | Function for computing the Linear Weights
long2wide.fn | long2wide.fn: This function transforms a 3-column dataset of frequencies to a square matrix or a contingency table. This function uses the freq.supp.fn() function.
ordinal.weights | Function for computing the Ordinal Weights
pa.coeff.dist | Percent agreement coefficient among multiple raters (2, 3, +) when the input dataset is the distribution of raters by subject and category.
pa.coeff.raw | Percent agreement among multiple raters (2, 3, +) when the input data represent the raw ratings reported for each subject and each rater.
pa2.table | Percent Agreement coefficient for 2 raters
quadratic.weights | Function for computing the Quadratic Weights
radical.weights | Function for computing the Radical Weights
ratio.weights | Function for computing the Ratio Weights
scott2.table | Scott's coefficient for 2 raters
trim | An r function for trimming leading and trealing blanks
x.dist10x5 | Dataset of categorical ratings assigned to 10 subjects and presented in the form of a distribution of 4 raters by subject and category
x.dist6x5psy | Dataset showing how 6 psychiatrists classified 15 patients by their mental health condition.
x.raw10x4 | Raw categorical ratings assigned to 10 subjects by 4 raters
x.raw12x4 | This dataset contains raw categorical ratings that 4 raters assigned to 12 subjects.