#' Tschuprow's T
#'
#' Calculate Tschuprow's T on a contingency table.
#'
#' @param x Matrix - contingency table
#'
#' @return Hypothesis test result showing results of test.
cor.tschuprow.tc <- function(
x
) {
chi.sq.result <- chisq.test(x, correct = F)
chi <- rmnames(chi.sq.result$statistic)
p <- nrow(x) - 1
q <- ncol(x) - 1
t.c <- sqrt(chi / (sum(x) * sqrt(p*q)))
retval<-list(data.name = "data",
statistic = c(t.c = t.c),
estimate = c( max.possible.t.c = min(p,q)/max(p,q)
#,max.possible.phi.squared = q-1
,chi.square = rmnames(chi.sq.result$statistic)
,chi.square.df = (nrow(x)-1)*(ncol(x)-1)
,chi.square.p = rmnames(chi.sq.result$p.value)
),
parameter = 0 ,
p.value = chi.sq.result$p.value,
null.value = 0,
alternative = "two.sided",
method = "Pearson Phi and Pearson Chi-Squared"#,
# conf.int = c(NA,NA)
)
names(retval$null.value) <- "phi"
names(retval$parameter) <- "null hypothesis phi"
class(retval)<-"htest"
retval
}
#' @rdname cor.tschuprow.tc
cor.chuprov.tc <- cor.tschuprow.tc
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