paik {asbio} R Documentation

## Paik diagrams

### Description

Paik diagrams for the representation of Simpsons Paradox in three way tables.

### Usage

```
paik(formula, counts, resp.lvl = 2, data, circle.mult = 0.4, xlab = NULL,
ylab = NULL, leg.title = NULL, leg.loc = NULL, show.mname = FALSE,...)
```

### Arguments

 `formula` A two sided formula, e.g. `Y ~ X1 + X2`, with cross-classified categorical variables. The second explanatory variable, i.e. `X2`, is used as the trace variable whose levels are distinguished in the graph with different colors. Interactions and nested terms are not allowed. `counts` A vector of counts for the associated categorical variables in `formula`. `resp.lvl` The level in Y of primary interest. See example below. `data` Dataframe containing variables in `formula`. `circle.mult` Multiplier for circle radii in the diagram. `xlab` X-axis label. By default this is defined as the categories in the first explanatory variable, `X1`. `ylab` Y-axis label. By default these will be proportions with respect to the specified level of interest in the response. `leg.title` Legend title. By default the conditioning variable name. `leg.loc` Legend location. A `legend` location keyword; `"bottomright"`, `"bottom"`, `"bottomleft"`, `"left"`, `"topleft"`, `"top"`, `"topright"`, `"right"` or `"center"`. `show.mname` Logical, indicating whether or not the words "Marginal prop" should printed in the graph above the dotted line indicating marginal proportions. `...` Additional arguments from `plot`.

Ken Aho

### References

Agresti, A. (2012) Categorical Data Analysis, 3rd edition. New York. Wiley.

Paik M. (1985) A graphical representation of a three-way contingency table: Simpson's paradox and correlation. American Statistician 39:53-54.

### Examples

```require(tcltk)

data(death.penalty)# from Agresti 2012

op <- par(mfrow=c(1,2), mar=c(4,4,0,0))
paik(verdict ~ d.race + v.race, counts = count, data = death.penalty,
leg.title = "Victims race", xlab = "Defendants race",
ylab = "Proportion receiving death penalty")
par(mar=c(4,2,0,2))
paik(verdict ~ v.race + d.race, counts = count, data = death.penalty,
xlab = "Victims race", leg.title = "Defendants race",leg.loc="topleft",
ylab = "", yaxt = "n")