# Title: Dependency Analysis
# Objective: Dependency analysis w.r.t. a categorical field & a categorical target
# Created by: greyhypotheses
# Created on:
IsDependentCC <- function(variables, target, frame){
#' Returns a table of test statistic, p, & Cramér's V values
#'
#' @param variables: The list of categorical fields
#' @param target: The target field
#' @param frame: The table of data
estimates <- data.table()
for (variable in variables) {
writeLines(paste0('\n\nCase: ', variable))
frequencies <- table(frame[[variable]], frame[[target]])
print(frequencies)
# In relation to a categrical field in question, is the classification of an instance independent of the
# categories/elements of the field?
chisquared <- chisq.test(frequencies, simulate.p.value = TRUE, B = 5000)
# In relation to a categrical field in question, what is the degree of association between the classification options &
# the categories/elements of the field?
cramercinq <- rcompanion::cramerV(frequencies, y = NULL, ci = FALSE, conf = 0.95, type = 'bca',
R = 1000, histogram = FALSE, digits = 4, bias.correct = TRUE)
# Add the estimates to the table of estimates
calculations <- data.table(field = variable, chi_squared_statistic = chisquared$statistic,
pvalue = chisquared$p.value, cramerv = cramercinq)
estimates <- rbind(estimates, calculations)
}
return(estimates)
}
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