How to get a data.frame with cases from a contingency table in r?

Question

I would like to reproduce some calculations from a book (logit regression). The book gives a contingency table and the results.

Here is the Table:

    .


    example <- matrix(c(21,22,6,51), nrow = 2, byrow = TRUE)
    #Labels:
    rownames(example) <- c("Present","Absent")
    colnames(example) <- c(">= 55", "<55")

It gives me this:

            >= 55 <55
    Present    21  22
    Absent      6  51

But to use the glm()-function the data has to be in the following way:

(two colums, one with "Age", and one with "Present", filled with 0/1)

    age <- c(rep(c(0),27), rep(c(1),73))
    present <- c(rep(c(0),21), rep(c(1),6), rep(c(0),22), rep(c(1),51))

    data <- data.frame(present, age)

    > data
        present age
    1         0   0
    2         0   0
    3         0   0
    .         .   .
    .         .   .
    .         .   .
    100       1   1

Is there a simple way to get this structure from the table/matrix?

Answer 1

reshape2::melt(example)

This will give you,

     Var1  Var2 value
1 Present >= 55    21
2  Absent >= 55     6
3 Present   <55    22
4  Absent   <55    51

which you can easily use for glm

Answer 2

You could perhaps use the countsToCases function as defined here.

countsToCases(as.data.frame(as.table(example))) 
#        Var1  Var2
#1    Present >= 55
#1.1  Present >= 55
#1.2  Present >= 55
#1.3  Present >= 55
#1.4  Present >= 55
#1.5  Present >= 55
# ...

You can always recode the variables to numeric afterwards, if you prefer.