## Version 0.7.4

### Bug fixed

1. Allowing model_order accurately work when relabel_predictors is used.
2. Letting the vignette correctly shown.

## Version 0.7.3

### New features

1. Adding argument model_order and submodel_order in small_multiple to allow customizing the order of models to present.
2. Adding argument axis_switch in small_multiple to allow switching the positions of the variable labels and y axis ticks.

## Version 0.7.1

### Bug fixed

1. Fixed the error when setting style = "distribution". Thanks for Indrajee @IndrajeetPatil pointing that out.

## Version 0.7.0

### New features

1. Adding argument model_order in dwplot to allow customizing the order of models to present.
2. Adding argument fontSize in add_brackets to allow customizing the font size of bracket labels, and opening possibility for users to further customize bracket labels.
3. Using the parameters instead of broomExtra as the plotting data frame creator. Thanks for the suggestion from @IndrajeetPatil.

### Bug fixed

1. Models and margins present in the correct order.

## Version 0.6.0

### New features

1. Adding changing the dw_tidy engine to broomExtra::tidy_parapmeter. Thanks for Indrajeet Patil’s amazing package.
2. Adding the function to plot AME based on margins::margins.

### Bug fixed

1. Allowing the data.frame output varying based on confidence intervals.
2. Setting the default value of by_2sd to FALSE.

## Version 0.5.0

#### New features

1. The 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 code.

2. 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:


library(dotwhisker)

# linear model of interest
lm_object <- stats::lm(formula = wt ~ am * cyl, data = mtcars)

# 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).

## Version 0.4.1

#### Bug fixes

1. Fixed a bug in add_brackets() that caused brackets to overlap in large models or when many models were included in a single plot.

## Version 0.4.0

#### New features

1. A new plot style! Specifying style = "distribution" in the arguments to dwplot() presents regression coefficients as normal distributions, underscored with a line representing the desired confidence interval.
2. relabel_predictors() now conveniently reorders the predictors as well.
3. 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 ({ and }) before piping them to add_brackets()!

#### Syntax changes

1. The alpha argument to dwplot() should no longer be used to change the width of confidence intervals; use conf.int (to be passed to broom::tidy via ...) instead.
2. When 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.

#### Bug fixes

1. Fixed a bug in add_brackets() that de-centered the brackets
2. Fixed a bug that caused dot_args to be ignored after plots were passed to relabel_predictors()
3. Fixed a bug that prevented small_multiple() from directly reading confidence intervals from a model.
4. Fixed a bug in 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 inspiring style = "distribution"!

## Version 0.3.0

1. Rewrote the plotting functions based on the ggstance functions. The new dwplot allows cooperating with more ggplot functions, such as facet_*.
2. Drew whiskers based on the CI estimates directly from the model output. See more details in tidy.lm) and confint.
3. Clarified the description of by_2sd.

## Version 0.2.6

1. Fixed the bug in relabel_predictors.

## Version 0.2.5

1. Expanded capabilities of relabel_predictors. relabel_predictors now accepts plots as well as tidy dataframes as input; that is, it may now be used both before and after calls to dwplot.
2. Deprecated relabel_y_axis. It is easy to mistakenly mislabel variables with relabel_y_axis, and it has a conflict with add_brackets in single-model plots.
3. Provided example of using multiple shapes for multiple models in vignette.
4. dwplot works for polr projects.

## Version 0.2.4

1. Improved the presentation of small_multiple.

## Version 0.2.3

1. Fixed the error of variable ordering with a single model.

## Version 0.2.2

1. Fixed the error in presenting multiple models.

## Version 0.2.1

1. Fixed the error due to the update of dplyr::group_by
2. Fixing the errors in vignette.
3. Adding the show_intercept argument.
4. Shorten the version number to three digits as devtools suggests.

## Version 0.2.0.5

1. Fixed the error due to the update of gridExtra.
2. Fixed the error due to the update of ggplot2.

## Version 0.2.0.4

1. Fixed presenting error in multilevel models (#44)

## Version 0.2.0.3

1. Fixed the link error in kl2007_example.Rmd.

## Version 0.2.0.2

1. Improving the vignette.
2. The function works for ggplot2 2.0.0.

## Version 0.2.0.1

1. Fixed the error in the vignette.

## Version 0.2.0.0

1. Allowing directly using model objects besides tidy data.frame.
2. Adding two new special plotting functions: secret_weapon and small_multiple.
3. Adding two graph adjusting functions: relabel_predictor and relabel_y_axis.

More details about the new functions are available in the vignette.