library(MASS)
TeaTasting <- matrix(c(3, 1, 1, 3), nrow = 2,
dimnames = list(Guess = c("Milk", "Tea"),
Truth = c("Milk", "Tea"))
)
## compute maximum statistic
coindep_test(TeaTasting)
## compute Chi-squared statistic
coindep_test(TeaTasting, indepfun = function(x) sum(x^2))
## use unconditional asymptotic distribution
chisq.test(TeaTasting, correct = FALSE)
chisq.test(TeaTasting)
data("UCBAdmissions")
## double maximum statistic
coindep_test(UCBAdmissions, margin = "Dept")
## maximum of Chi-squared statistics
coindep_test(UCBAdmissions, margin = "Dept", indepfun = function(x) sum(x^2))
## Pearson Chi-squared statistic
coindep_test(UCBAdmissions, margin = "Dept", indepfun = function(x) sum(x^2), aggfun = sum)
## use unconditional asymptotic distribution
loglm(~ Dept * (Gender + Admit), data = UCBAdmissions)
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