# multicomp.plot: Multiple Comparison Plot In arm: Data Analysis Using Regression and Multilevel/Hierarchical Models

## Description

Plots significant difference of simulated array.

## Usage

 ```1 2 3 4 5 6``` ```multicomp.plot(object, alpha = 0.05, main = "Multiple Comparison Plot", label = NULL, shortlabel = NULL, show.pvalue = FALSE, label.as.shortlabel = FALSE, label.on.which.axis = 3, col.low = "lightsteelblue", col.same = "white", col.high = "lightslateblue", vertical.line = TRUE, horizontal.line = FALSE, vertical.line.lty = 1, horizontal.line.lty = 1, mar=c(3.5,3.5,3.5,3.5)) ```

## Arguments

 `object` Simulated array of coefficients, columns being different variables and rows being simulated result. `alpha` Level of significance to compare. `main` Main label. `label` Labels for simulated parameters. `shortlabel` Short labels to put into the plot. `show.pvalue` Default is FALSE, if set to TRUE replaces short label with Bayesian p value. `label.as.shortlabel` Default is FALSE, if set to TRUE takes first 2 character of label and use it as short label. `label.on.which.axis` default is the 3rd (top) axis. `col.low` Color of significantly low coefficients. `col.same` Color of not significant difference. `col.high` Color of significantly high coefficients. `vertical.line` Default is TRUE, if set to FALSE does not draw vertical line. `horizontal.line` Default is FALSE, if set to TRUE draws horizontal line. `vertical.line.lty` Line type of vertical line. `horizontal.line.lty` Line type of horizontal line. `mar` A numerical vector of the form `c(bottom, left, top, right)` which gives the number of lines of margin to be specified on the four sides of the plot. The default is `c(3.5,3.5,3.5,3.5)`.

## Value

 `pvalue` Array of Bayesian p value. `significant` Array of significance.

## Author(s)

Masanao Yajima [email protected], Andrew Gelman [email protected]

## References

Andrew Gelman and Jennifer Hill. (2006). Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge University Press.

`coefplot`

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20``` ```old.par <- par(no.readonly = TRUE) # example 1 simulation.array <- data.frame(coef1=rnorm(100,10,2), coef2=rnorm(100,5,2), coef3=rnorm(100,0,1), coef4=rnorm(100,-5,3), coef5=rnorm(100,-2,1)) short.lab <- c("c01", "c02", "c03", "c04", "c05") multicomp.plot(simulation.array[,1:4], label.as.shortlabel=TRUE) # wraper for multicomp.plot mcplot(simulation.array, shortlabel = short.lab) # example 2 data(lalonde) M1 <- lm(re78 ~ treat + re74 + re75 + age + educ + u74 + u75, data=lalonde) M1.sim <- sim(M1) lm.sim <- coef(M1.sim)[,-1] multicomp.plot(lm.sim, label.as.shortlabel=TRUE, label.on.which.axis=2) par(old.par) ```

### Example output

```Loading required package: MASS