# Create r x c contigency table (exposure levels vs. binary outcome)

### Description

Create r x c contigency table for r exposure levels and c outcome levels

### Usage

1 2 |

### Arguments

`...` |
see details |

`ncol` |
number of columns = 2 (default) when a table is constructed from a vector or sequence of numbers |

`byrow` |
Default is TRUE and single vector or collection of numbers is read in row-wise. Set to FALSE to read in column-wise. |

`rev` |
reverse order of "rows", "colums", "both", or "neither" (default) |

### Details

Creates r x 2 table with r exposure levels and 2 outcome levels (No vs. Yes). Arguments can be one of the following:

(1) four or more integers that be converted into r x 2 table (the number of integers must be even),

(2) two categorical vectors (1st vector is exposure with r levels, 2nd vector is outcome with 2 levels),

(3) r x 2 contingency table, or

(4) single vector that be converted into r x 2 table (the number of integers must be even).

The contingency table created by this function is usually used for
additional analyses, for example, the `epitab`

function.

### Value

Returns r x 2 contingency table, usually for additional analyses.

### Note

Visit http://medepi.com for the latest.

### Author(s)

Tomas Aragon, aragon@berkeley.edu, http://www.medepi.com

### References

none

### See Also

`epitable`

### Examples

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ```
## single vector
dat <- c(88, 20, 555, 347)
epitable(dat)
## 4 or more integers
epitable(1,2,3,4,5,6)
## single matrix
epitable(matrix(1:6, 3, 2))
## two categorical vectors
exposure <- factor(sample(c("Low", "Med", "High"), 100, rep=TRUE),
levels=c("Low", "Med", "High"))
outcome <- factor(sample(c("No", "Yes"), 100, rep=TRUE))
epitable(exposure, outcome)
epitable("Exposure"=exposure, "Disease"=outcome)
## reversing row and/or column order
zz <- epitable("Exposure Level"=exposure, "Disease"=outcome)
zz
epitable(zz, rev = "r")
epitable(zz, rev = "c")
epitable(zz, rev = "b")
``` |