creating 3-way tables for mantelhaen.test
Taka,
Maybe you did something strange when you "replaced Y1's values ....".
Is the result a 10-level factor?
The following works for me.
x1 <- sample(c("y", "n"), 100, replace = TRUE)
x2 <- sample(c("a", "b"), 100, replace = TRUE)
y <- sample(1:10, 100, replace = TRUE)
y <- factor(y)
dat <- data.frame(x1, x2, y)
dat.xt <- xtabs(~ x1 + x2 + y, data = dat)
mantelhaen.test(dat.xt)
Peter Ehlers
Taka Matzmoto wrote:
Hi R users I have serveral binary variables (e.g., X1, X2, X3, X4, X5, X,6, and X7) and one continuous variable (e.g., Y1). I combined these variables using data.frame() mydata <- data.frame(X1,X2,X3,X4,X5,X6,X7,Y1) after that, I sorted this data.frame rank.by.Y1<-order(mydata[,8]) sorted.mydata<-mydata[rank.by.Y1,] after that, I replaced Y1's values with values ranging from 1 to 10 ( 1 represents the lowest group on Y1 and 10 presents the hight group on Y1). Now Y1 becomes a grouping variable. What I like to do is to apply mantelhaen.test for each binary variable pair (e.g, X1 and X2, X1 and X3, X1 and X4, .... , X6 and X7) In order to apply mantelhaen.test, a 3-dimensional contingency table is required. Could you provide some advice on how to create a 3-dimensional contingency table (first dimension represents the first variable of variable pair, second dimension the second variable of variable pair, and third dimension represents 1 to 10 ) and apply mantelhaen.test ? I looked at arrary, xtabs, table commands but I couldn't figure out yet. Thank you
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