Title: Techniques to Build Better Balance
Version: 0.1.0
Description: Build better balance in causal inference models. 'halfmoon' helps you assess propensity score models for balance between groups using metrics like standardized mean differences and visualization techniques like mirrored histograms. 'halfmoon' supports both weighting and matching techniques.
License: MIT + file LICENSE
URL: https://github.com/r-causal/halfmoon, https://r-causal.github.io/halfmoon/
BugReports: https://github.com/r-causal/halfmoon/issues
Depends: R (≥ 2.10)
Imports: cli, ggplot2, tidyselect, tidysmd (≥ 0.2.0)
Suggests: covr, testthat (≥ 3.0.0), vdiffr
Config/testthat/edition: 3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.3
NeedsCompilation: no
Packaged: 2023-05-30 17:15:48 UTC; malcolmbarrett
Author: Malcolm Barrett ORCID iD [aut, cre, cph]
Maintainer: Malcolm Barrett <malcolmbarrett@gmail.com>
Repository: CRAN
Date/Publication: 2023-05-30 18:20:02 UTC

Calculate weighted and unweighted empirical cumulative distributions

Description

The empirical cumulative distribution function (ECDF) provides an alternative visualization of distribution. geom_ecdf() is similar to ggplot2::stat_ecdf() but it can also calculate weighted ECDFs.

Usage

geom_ecdf(
  mapping = NULL,
  data = NULL,
  geom = "step",
  position = "identity",
  ...,
  n = NULL,
  pad = TRUE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

Set of aesthetic mappings created by aes(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

A function will be called with a single argument, the plot data. The return value must be a data.frame, and will be used as the layer data. A function can be created from a formula (e.g. ~ head(.x, 10)).

geom

The geometric object to use to display the data, either as a ggproto Geom subclass or as a string naming the geom stripped of the geom_ prefix (e.g. "point" rather than "geom_point")

position

Position adjustment, either as a string naming the adjustment (e.g. "jitter" to use position_jitter), or the result of a call to a position adjustment function. Use the latter if you need to change the settings of the adjustment.

...

Other arguments passed on to layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like colour = "red" or size = 3. They may also be parameters to the paired geom/stat.

n

if NULL, do not interpolate. If not NULL, this is the number of points to interpolate with.

pad

If TRUE, pad the ecdf with additional points (-Inf, 0) and (Inf, 1)

na.rm

If FALSE (the default), removes missing values with a warning. If TRUE silently removes missing values.

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. borders().

Value

a geom

Aesthetics

In addition to the aesthetics for ggplot2::stat_ecdf(), geom_ecdf() also accepts:

Examples

library(ggplot2)

ggplot(
  nhefs_weights,
  aes(x = smokeyrs, color = qsmk)
) +
  geom_ecdf(aes(weights = w_ato)) +
  xlab("Smoking Years") +
  ylab("Proportion <= x")

Create mirrored histograms

Description

Create mirrored histograms

Usage

geom_mirror_histogram(
  mapping = NULL,
  data = NULL,
  position = "stack",
  ...,
  binwidth = NULL,
  bins = NULL,
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

Set of aesthetic mappings created by aes(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

A function will be called with a single argument, the plot data. The return value must be a data.frame, and will be used as the layer data. A function can be created from a formula (e.g. ~ head(.x, 10)).

position

Position adjustment, either as a string naming the adjustment (e.g. "jitter" to use position_jitter), or the result of a call to a position adjustment function. Use the latter if you need to change the settings of the adjustment.

...

Other arguments passed on to layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like colour = "red" or size = 3. They may also be parameters to the paired geom/stat.

binwidth

The width of the bins. Can be specified as a numeric value or as a function that calculates width from unscaled x. Here, "unscaled x" refers to the original x values in the data, before application of any scale transformation. When specifying a function along with a grouping structure, the function will be called once per group. The default is to use the number of bins in bins, covering the range of the data. You should always override this value, exploring multiple widths to find the best to illustrate the stories in your data.

The bin width of a date variable is the number of days in each time; the bin width of a time variable is the number of seconds.

bins

Number of bins. Overridden by binwidth. Defaults to 30.

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

orientation

The orientation of the layer. The default (NA) automatically determines the orientation from the aesthetic mapping. In the rare event that this fails it can be given explicitly by setting orientation to either "x" or "y". See the Orientation section for more detail.

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. borders().

Value

a geom

Examples

library(ggplot2)
ggplot(nhefs_weights, aes(.fitted)) +
  geom_mirror_histogram(
    aes(group = qsmk),
    bins = 50
  ) +
  geom_mirror_histogram(
    aes(fill = qsmk, weight = w_ate),
    bins = 50,
    alpha = 0.5
  ) +
  scale_y_continuous(labels = abs)

NHEFS with various propensity score weights

Description

A dataset containing various propensity score weights for causaldata::nhefs_complete.

Usage

nhefs_weights

Format

A data frame with 1566 rows and 14 variables:

qsmk

Quit smoking

race

Race

age

Age

sex

Sex

education

Education level

smokeintensity

Smoking intensity

smokeyrs

Number of smoke-years

exercise

Exercise level

active

Daily activity level

wt71

Participant weight in 1971 (baseline)

w_ate

ATE weight

w_att

ATT weight

w_atc

ATC weight

w_atm

ATM weight

w_ato

ATO weight

.fitted

Propensity score

Objects exported from other packages

Description

These objects are imported from other packages. Follow the links below to see their documentation.

tidyselect

contains, ends_with, everything, last_col, matches, num_range, one_of, peek_vars, starts_with

tidysmd

bind_matches, geom_love, love_plot, tidy_smd