# fourfoldplot

0th

Percentile

##### Fourfold Plots

Creates a fourfold display of a 2 by 2 by $k$ contingency table on the current graphics device, allowing for the visual inspection of the association between two dichotomous variables in one or several populations (strata).

Keywords
hplot
##### Usage
fourfoldplot(x, color = c("#99CCFF", "#6699CC"),
conf.level = 0.95,
std = c("margins", "ind.max", "all.max"),
margin = c(1, 2), space = 0.2, main = NULL,
mfrow = NULL, mfcol = NULL)
##### Arguments
x

a 2 by 2 by $k$ contingency table in array form, or as a 2 by 2 matrix if $k$ is 1.

color

a vector of length 2 specifying the colors to use for the smaller and larger diagonals of each 2 by 2 table.

conf.level

confidence level used for the confidence rings on the odds ratios. Must be a single nonnegative number less than 1; if set to 0, confidence rings are suppressed.

std

a character string specifying how to standardize the table. Must match one of "margins", "ind.max", or "all.max", and can be abbreviated to the initial letter. If set to "margins", each 2 by 2 table is standardized to equate the margins specified by margin while preserving the odds ratio. If "ind.max" or "all.max", the tables are either individually or simultaneously standardized to a maximal cell frequency of 1.

margin

a numeric vector with the margins to equate. Must be one of 1, 2, or c(1, 2) (the default), which corresponds to standardizing the row, column, or both margins in each 2 by 2 table. Only used if std equals "margins".

space

the amount of space (as a fraction of the maximal radius of the quarter circles) used for the row and column labels.

main

character string for the fourfold title.

mfrow

a numeric vector of the form c(nr, nc), indicating that the displays for the 2 by 2 tables should be arranged in an nr by nc layout, filled by rows.

mfcol

a numeric vector of the form c(nr, nc), indicating that the displays for the 2 by 2 tables should be arranged in an nr by nc layout, filled by columns.

##### Details

The fourfold display is designed for the display of 2 by 2 by $k$ tables.

Following suitable standardization, the cell frequencies $f_{ij}$ of each 2 by 2 table are shown as a quarter circle whose radius is proportional to $\sqrt{f_{ij}}$ so that its area is proportional to the cell frequency. An association (odds ratio different from 1) between the binary row and column variables is indicated by the tendency of diagonally opposite cells in one direction to differ in size from those in the other direction; color is used to show this direction. Confidence rings for the odds ratio allow a visual test of the null of no association; the rings for adjacent quadrants overlap if and only if the observed counts are consistent with the null hypothesis.

Typically, the number $k$ corresponds to the number of levels of a stratifying variable, and it is of interest to see whether the association is homogeneous across strata. The fourfold display visualizes the pattern of association. Note that the confidence rings for the individual odds ratios are not adjusted for multiple testing.

##### References

Friendly, M. (1994). A fourfold display for 2 by 2 by $k$ tables. Technical Report 217, York University, Psychology Department. http://www.math.yorku.ca/SCS/Papers/4fold/4fold.ps.gz

mosaicplot
library(graphics) ## Use the Berkeley admission data as in Friendly (1995). x <- aperm(UCBAdmissions, c(2, 1, 3)) dimnames(x)[[2]] <- c("Yes", "No") names(dimnames(x)) <- c("Sex", "Admit?", "Department") stats::ftable(x) ## Fourfold display of data aggregated over departments, with ## frequencies standardized to equate the margins for admission ## and sex. ## Figure 1 in Friendly (1994). fourfoldplot(margin.table(x, c(1, 2))) ## Fourfold display of x, with frequencies in each table ## standardized to equate the margins for admission and sex. ## Figure 2 in Friendly (1994). fourfoldplot(x) ## Fourfold display of x, with frequencies in each table ## standardized to equate the margins for admission. but not ## for sex. ## Figure 3 in Friendly (1994). fourfoldplot(x, margin = 2)