Computes the Cram<e9>r's association coefficient between 2 nominal variables, its confidence interval (by bootstraping) and tests for its significance.
Usage
cramer.test(x, y, nrep = 1000, conf.level = 0.95)
Arguments
x
a contingency table ('matrix' or 'table' object). x and y can also both be factors.
y
ignored if x is a contingency table. If not, y should be a vector of the same length.
nrep
number of replicates for bootstraping.
conf.level
confidence level.
Value
method
name of the test.
statistic
test statistics.
parameter
test degrees of freedom.
p.value
test p-value.
data.name
a character string giving the names of the data.
estimate
Cram<e9>r's coefficient.
conf.level
confidence level.
rep
number of replicates.
conf.int
confidence interval.
alternative
a character string giving the alternative hypothesis, always "two.sided"
null.value
the value of the association measure under the null hypothesis, always 0.
# NOT RUN {var1 <- sample(LETTERS[1:3],30,replace=TRUE)
var2 <- sample(letters[1:3],30,replace=TRUE)
cramer.test(var1,var2)
# or cramer.test(table(var1,var2))# }