pa2.table: Percent Agreement coefficient for 2 raters

In irrCAC: Computing Chance-Corrected Agreement Coefficients (CAC)

Description

Percent Agreement coefficient for 2 raters

Usage

pa2.table(ratings, weights = identity.weights(1:ncol(ratings)),
  conflev = 0.95, N = Inf)

Arguments

ratings	A square table of ratings (assume no missing ratings).
weights	An optional matrix that contains the weights used in the weighted analysis. By default, this parameter contaings the identity weight matrix, which leads to the unweighted analysis.
conflev	An optional parameter that specifies the confidence level used for constructing confidence intervals. By default the function assumes the standard value of 95%.
N	An optional parameter representing the finite population size if any. It is used to perform the finite population correction to the standard error. It's default value is infinity.

Value

A data frame containing the following 5 variables: coeff.name coeff.val coeff.se coeff.ci coeff.pval.

Examples

#The dataset "cont3x3abstractors" comes with this package. Analyze it as follows:
pa2.table(cont3x3abstractors) #Yields percent agreement along with precision measures
pa <- pa2.table(cont3x3abstractors)$coeff.val #Yields percent agreement alone.
pa
q <- nrow(cont3x3abstractors) #Number of categories
pa2.table(cont3x3abstractors,weights = quadratic.weights(1:q)) #Weighted percent agreement

Example output

         coeff.name coeff.val   coeff.se      coeff.ci coeff.pval
1 Percent Agreement      0.89 0.03128898 (0.828,0.952)      0e+00
[1] 0.89
         coeff.name coeff.val    coeff.se      coeff.ci coeff.pval
1 Percent Agreement    0.9725 0.007822244 (0.957,0.988)      0e+00

irrCAC documentation built on Sept. 23, 2019, 5:05 p.m.