bamdit (version 3.4.4)

plotcompare: plotcompare

Description

This function compares the predictive posterior surfaces of two fitted models.

Usage

plotcompare(
  m1,
  m2,
  level = 0.95,
  title = paste("Comparative Predictive Posterior Contours"),
  m1.name = "Model.1",
  m2.name = "Model.2",
  group = NULL,
  limits.x = c(0, 1),
  limits.y = c(0, 1),
  group.colors = c("blue", "red")
)

Arguments

m1

A model fitted to the data. This is an object generated by the metadiag function.

m2

A second model fitted to the data. This is an object generated by the metadiag function.

level

Credibility level of the predictive curves.

title

The title of the plot.

m1.name

Label of the model 1.

m2.name

Label of the model 2.

group

An optional argument, which is a variable name indicating a group factor. This argument is used to compare results from two subgroups.

limits.x

A vector with the limits of the horizontal axis.

limits.y

A vector with the limits of the vertical axis.

group.colors

A character vector with two color names.

See Also

metadiag.

Examples

## execute analysis
if (FALSE) {

# Comparing results from two models same data

data(glas)
glas.t <- glas[glas$marker == "Telomerase", 1:4]
glas.m1 <- metadiag(glas.t)
glas.m2 <- metadiag(glas.t, re = "sm")
plotcompare(m1 = glas.m1, m2 = glas.m2)

# Comparing results from two models fitted to two subgroups of data:
# studies with retrospective design and studies with prospective design

data("ct")
ct$design = factor(ct$design, labels = c("Prospective", "Retrospective"))

m1.ct <- metadiag(ct[ct$design=="Prospective", ])
m2.ct <- metadiag(ct[ct$design=="Retrospective", ])

plotcompare(m1.ct, m2.ct,m1.name = "Retrospective design",
m2.name = "Prospective design",group = "design",
limits.x = c(0, 0.75), limits.y = c(0.65, 1))


}