DescTools (version 0.99.19)

CochranArmitageTest: Cochran-Armitage Test for Trend

Description

Perform a Cochran Armitage test for trend in binomial proportions across the levels of a single variable. This test is appropriate only when one variable has two levels and the other variable is ordinal. The two-level variable represents the response, and the other represents an explanatory variable with ordered levels. The null hypothesis is the hypothesis of no trend, which means that the binomial proportion is the same for all levels of the explanatory variable.

Usage

CochranArmitageTest(x, alternative = c("two.sided", "increasing", "decreasing"))

Arguments

x

a frequency table or a matrix.

alternative

a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "increasing" or "decreasing". You can specify just the initial letter.

Value

htest, containing the following components:

References

Agresti, A. (2002) Categorical Data Analysis. John Wiley & Sons

See Also

prop.trend.test

Examples

# http://www.lexjansen.com/pharmasug/2007/sp/sp05.pdf, pp. 4
dose <- matrix(c(10,9,10,7, 0,1,0,3), byrow=TRUE, nrow=2, dimnames=list(resp=0:1, dose=0:3))
Desc(dose)

CochranArmitageTest(dose, "increasing")
CochranArmitageTest(dose)
CochranArmitageTest(dose, "decreasing")


# not exactly the same as in package coin:
# independence_test(tumor ~ dose, data = lungtumor, teststat = "quad")
lungtumor <- data.frame(dose = rep(c(0, 1, 2), c(40, 50, 48)),
                        tumor = c(rep(c(0, 1), c(38, 2)),
                                  rep(c(0, 1), c(43, 7)),
                                  rep(c(0, 1), c(33, 15))))
tab <- table(lungtumor$dose, lungtumor$tumor)
CochranArmitageTest(tab)

# but similar to
prop.trend.test(tab[,1], apply(tab,1, sum))