Model coefficients with broom and ggplot2
Plot the coefficients of a model with broom and ggplot2.
For an updated and improved version, see ggcoef_model().
ggcoef(
x,
mapping = aes_string(y = "term", x = "estimate"),
conf.int = TRUE,
conf.level = 0.95,
exponentiate = FALSE,
exclude_intercept = FALSE,
vline = TRUE,
vline_intercept = "auto",
vline_color = "gray50",
vline_linetype = "dotted",
vline_size = 1,
errorbar_color = "gray25",
errorbar_height = 0,
errorbar_linetype = "solid",
errorbar_size = 0.5,
sort = c("none", "ascending", "descending"),
...
)x |
a model object to be tidied with |
mapping |
default aesthetic mapping |
conf.int |
display confidence intervals as error bars? |
conf.level |
level of confidence intervals (passed to |
exponentiate |
if |
exclude_intercept |
should the intercept be excluded from the plot? |
vline |
print a vertical line? |
vline_intercept |
|
vline_color |
color of the vertical line |
vline_linetype |
line type of the vertical line |
vline_size |
size of the vertical line |
errorbar_color |
color of the error bars |
errorbar_height |
height of the error bars |
errorbar_linetype |
line type of the error bars |
errorbar_size |
size of the error bars |
sort |
|
... |
additional arguments sent to |
# Small function to display plots only if it's interactive p_ <- GGally::print_if_interactive library(broom) reg <- lm(Sepal.Length ~ Sepal.Width + Petal.Length + Petal.Width, data = iris) p_(ggcoef(reg)) d <- as.data.frame(Titanic) reg2 <- glm(Survived ~ Sex + Age + Class, family = binomial, data = d, weights = d$Freq) ggcoef(reg2, exponentiate = TRUE) ggcoef( reg2, exponentiate = TRUE, exclude_intercept = TRUE, errorbar_height = .2, color = "blue", sort = "ascending" )
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