multicomp.plot: Multiple Comparison Plot

In arm: Data Analysis Using Regression and Multilevel/Hierarchical Models

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 [e-mail], Andrew Gelman [e-mail]

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)
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)

arm documentation built on Aug. 29, 2022, 1:05 a.m.