multicomp.plot {arm} | R Documentation |
Plots significant difference of simulated array.
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))
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) . |
pvalue |
Array of Bayesian p value. |
significant |
Array of significance. |
Masanao Yajima yajima@stat.columbia.edu, Andrew Gelman gelman@stat.columbia.edu
Andrew Gelman and Jennifer Hill. (2006). Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge University Press.
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)