multicomp.plot {arm}R Documentation

Multiple Comparison Plot

Description

Plots significant difference of simulated array.

Usage

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 yajima@stat.columbia.edu, Andrew Gelman gelman@stat.columbia.edu

References

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

See Also

coefplot

Examples

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)
lm.sim <- sim(M1)[["coef"]][,-1]
multicomp.plot(lm.sim, label.as.shortlabel=TRUE, label.on.which.axis=2)

par(old.par)

[Package arm version 1.2-8 Index]