MC.out.tabular: Tabular organization of accuracy and consistency output from...

View source: R/classification.R

MC.out.tabularR Documentation

Tabular organization of accuracy and consistency output from the LL.CA.MC() function.

Description

Function that takes the output from the LL.CA.MC() function and organizes it in a table with accuracy and consistency indices represented by columns and categories as rows.

Usage

MC.out.tabular(x)

Arguments

x

The list-output from the LL.CA.MC() function.

Examples

# Generate some fictional data. Say, 1000 individuals take a test with a
# maximum score of 100 and a minimum score of 0.
set.seed(1234)
p.success <- rBeta.4P(1000, 0.1, 0.95, 5, 3)
for (i in 1:100) {
  if (i == 1) {
    rawdata <- matrix(nrow = 1000, ncol = 100)
  }
  rawdata[, i] <- rbinom(1000, 1, p.success)
}

# Estimate accuracy and consistency where the lowest category are scores
# below 50, second lowest 60, then 70, 80, and 90. Using the cba() function
# to estimate the reliability of this test, to use the LL.CA.MC() function
# or estimating diagnostic performance and consistency indices of
# classifications when using several cut-points:
output <- LL.CA.MC(rowSums(rawdata), cba(rawdata), seq(50, 90, 10), 0, 100)

# As this output can get quite verbose as the number of categories increase,
# the MC.out.tabular() function can be used to organize the output more
# concisely in a tabular format.
MC.out.tabular(output)

betafunctions documentation built on May 29, 2024, 1:13 a.m.