plot_coef {mcmcsae}

Plot a set of model coefficients or predictions with uncertainty intervals based on summaries of simulation results or other objects.

Description

This function plots estimates with error bars. Multiple sets of estimates can be compared. The error bars can either be based on standard errors or on explicitly specified lower and upper bounds. The function is adapted from function plot.sae in package hbsae, which in turn was adapted from function coefplot.default from package arm.

Usage

plot_coef(
  ...,
  n.se = 1,
  est.names,
  sort.by = NULL,
  decreasing = FALSE,
  index = NULL,
  maxrows = 50L,
  maxcols = 6L,
  offset = 0.1,
  cex.var = 0.8,
  mar = c(0.1, 2.1, 5.1, 0.1)
)

Arguments

...

dc_summary objects (output by the summary method for simulation objects of class dc), sae objects (output by the functions of package hbsae), or lists. In case of a list the components used are those with name est for point estimates, se for standard error based intervals or lower and upper for custom intervals. Instead of dc_summary objects matrix objects are also supported as long as they contain columns named "Mean" and "SD" as do dc_summary objects. Named parameters of other types that do not match any other argument names are passed to lower-level plot functions.

n.se

number of standard errors below and above the point estimates to use for error bars. By default equal to 1. This only refers to the objects of class dc_summary and sae.

est.names

labels to use in the legend for the components of the ... argument

sort.by

vector by which to sort the coefficients, referring to the first object passed.

decreasing

if TRUE, sort in decreasing order (default).

index

vector of names or indices of the selected areas to be plotted.

maxrows

maximum number of rows in a column.

maxcols

maximum number of columns of estimates on a page.

offset

space used between plots of multiple estimates for the same area.

cex.var

the font size for the variable names, default=0.8.

mar

a numerical vector of the form c(bottom, left, top, right), specifying the number of lines of margin on each of the four sides of the plot.

Examples

# create artificial data
set.seed(21)
n <- 100
dat <- data.frame(
  x=runif(n),
  f=factor(sample(1:20, n, replace=TRUE))
)
model <- ~ reg(~ x, prior=pr_normal(precision=1), name="beta") + gen(factor=~f, name="v")
gd <- generate_data(model, data=dat)
dat$y <- gd$y
# fit a base model
model0 <- y ~ reg(~ 1, name="beta") + gen(factor=~f, name="v")
sampler <- create_sampler(model0, data=dat, block=TRUE)
sim <- MCMCsim(sampler, store.all=TRUE)
(summ0 <- summary(sim))
# fit 'true' model
model <- y ~ reg(~ x, name="beta") + gen(factor=~f, name="v")
sampler <- create_sampler(model, data=dat, block=TRUE)
sim <- MCMCsim(sampler, store.all=TRUE)
(summ <- summary(sim))
# compare random effect estimates against true parameter values
plot_coef(summ0$v, summ$v, list(est=gd$pars$v), n.se=2, offset=0.2,
  maxrows=10, est.names=c("base model", "true model", "true"))