model_orderaccurately work when
small_multipleto allow customizing the order of models to present.
small_multipleto allow switching the positions of the variable labels and y axis ticks.
style = "distribution". Thanks for Indrajee @IndrajeetPatil pointing that out.
dwplotto allow customizing the order of models to present.
add_bracketsto allow customizing the font size of bracket labels, and opening possibility for users to further customize bracket labels.
broomExtraas the plotting data frame creator. Thanks for the suggestion from @IndrajeetPatil.
broomExtra::tidy_parapmeter. Thanks for Indrajeet Patil’s amazing package.
vline argument is now available for
dwplot(). Passing a
geom_vline() object to
this argument, typically one with
xintercept = 0, will plot this line
behind the plotted coefficients, which most will find
aesthetically preferable. The default for this argument is
NULL, so if you prefer not to include such lines or just
like them plotted last and foremost, there’s no need to change your
dwplot() now again accepts the
whisker_arg argument to change the appearance of the
whiskers representing the confidence intervals that has been lost since
v0.3.0. This means you can, for example, specify different
colors for the dots and the whiskers:
# load the library library(dotwhisker) #> Loading required package: ggplot2 # linear model of interest <- stats::lm(formula = wt ~ am * cyl, data = mtcars) lm_object # creating the plot with dwplot dwplot(x = lm_object, dot_args = list(color = "red"), # color for the dot whisker_args = list(color = "black"), # color for the whisker vline = ggplot2::geom_vline(xintercept = 0, # put vline _behind_ coefs colour = "grey60", linetype = 2, size = 1))
Created on 2018-06-27 by the reprex package (v0.2.0).
add_brackets()that caused brackets to overlap in large models or when many models were included in a single plot.
style = "distribution"in the arguments to
dwplot()presents regression coefficients as normal distributions, underscored with a line representing the desired confidence interval.
relabel_predictors()now conveniently reorders the predictors as well.
add_brackets()can now be added directly to the end of a chain of commands that generate a dotwhisker plot; the intermediate object necessary in past versions is no longer needed. Just wrap the plotting commands in braces (
}) before piping them to
dwplot()should no longer be used to change the width of confidence intervals; use
conf.int(to be passed to
dwplot()is passed model objects rather than a tidy data frame, the regression coefficients are now rescaled by two standard deviations of their respective variables in the analyzed data (per
by_2sd()) by default. This may be changed by setting
by_2sd = FALSE.
add_brackets()that de-centered the brackets
dot_argsto be ignored after plots were passed to
small_multiple()from directly reading confidence intervals from a model.
by_2sd()now adjusts, if present, any confidence intervals in tidy data frames passed to the function.
Thanks to Steven V. Miller
and Ryan Burge for bug
reports, and to Ben Edwards and Jay Jacobs for
style = "distribution"!
ggstancefunctions. The new
dwplotallows cooperating with more
ggplotfunctions, such as
relabel_predictorsnow accepts plots as well as tidy dataframes as input; that is, it may now be used both before and after calls to
relabel_y_axis. It is easy to mistakenly mislabel variables with
relabel_y_axis, and it has a conflict with
add_bracketsin single-model plots.
More details about the new functions are available in the vignette.