Error bar and pointrange plot types

Description

Type function(s) for producing error bar and pointrange plots.

Usage

type_errorbar(length = 0.05, dodge = 0, fixed.pos = FALSE)

type_pointrange(dodge = 0, fixed.pos = FALSE)

Arguments

length	length of the edges of the arrow head (in inches).
dodge	Numeric value (>= 0) for dodging of overlapping by groups. Dodging is scaled relative to the x-axis tick locations (i.e., unique levels of x). For example, dodge = 0.5 would place the outermost dodged groups exactly midway the between axis ticks. Default value is 0 (no dodging).
fixed.pos	Logical indicating whether dodged groups should retain a fixed relative position based on their group value. Relevant for x categories that only have a subset of the total number of groups. Defaults to FALSE, in which case dodging is based on the number of unique groups present in that x category alone. See Examples.

Examples

library("tinyplot")

mod = lm(mpg ~ wt * factor(am), mtcars)
coefs = data.frame(names(coef(mod)), coef(mod), confint(mod))
colnames(coefs) = c("term", "est", "lwr", "upr")

op = tpar(pch = 19)

# "errorbar" and "pointrange" type convenience strings
tinyplot(est ~ term, ymin = lwr, ymax = upr, data = coefs, type = "errorbar")

tinyplot(est ~ term, ymin = lwr, ymax = upr, data = coefs, type = "pointrange")

# Use `type_errorbar()` to pass extra arguments for customization
tinyplot(est ~ term, ymin = lwr, ymax = upr, data = coefs,
         type = type_errorbar(length = 0.2))

# display three models side-by-side with dodging

models = list(
    "Model A" = lm(mpg ~ wt + cyl, data = mtcars),
    "Model B" = lm(mpg ~ wt + hp + cyl, data = mtcars),
    "Model C" = lm(mpg ~ wt, data = mtcars)
)

results = lapply(names(models), function(m) {
    data.frame(
        model = m,
        term = names(coef(models[[m]])),
        estimate = coef(models[[m]]),
        setNames(data.frame(confint(models[[m]])), c("conf.low", "conf.high"))
    )
})
results = do.call(rbind, results)

tinyplot(estimate ~ term | model,
         ymin = conf.low, ymax = conf.high,
         data = results,
         type = type_pointrange(dodge = 0.2))

# Note that the default dodged position is based solely on the number of
# groups (here: models) available to each coefficient term. To fix the
# position consistently across all terms, use `fixed.pos = TRUE`.

tinyplot(estimate ~ term | model,
         ymin = conf.low, ymax = conf.high,
         data = results,
         type = type_pointrange(dodge = 0.2, fixed.pos = TRUE))

tpar(op)