Version 3.4.1
Fixed a bug that would occur when imabalanced.only = TRUE in bal.tab but all variables were balanced.
Fixed a bug where the mean of a binary variable would be displayed as 1 minus its mean.
Fixed a bug that would occur when missingness patterns were the same for multiple variables.
Fixed a bug that would occur when a distance measure was to be assessed with bal.tab and there were missing values in the covariates (thanks to Laura Helmkamp).
Fixed a bug that would occur when estimand was supplied by the user when using the default method of bal.tab.
Fixed a bug where non-standard variable names (like "I(age^2)") would cause an error.
Fixed a bug where treatment levels that had different numbers of characters would yield an error.
Added disp.means option to bal.tab with continuous treatments.
Version 3.4.0
Added default method for bal.tab so it can be used with specially formatted output from other packages (e.g., from optweight). bal.plot should work with these outputs too. This, of course, will never be completely bug-free because infinite inputs are possible and cannot all be processed perfectly. Don’t try to break this function :)
Fixed some bugs occuring when standardized mean differences are not finite, thanks to Noémie Kiefer.
Speed improvements in bal.plot, especially with multiple facets, and in bal.tab.
Added new options to bal.plot, including the ability to display histograms rather than densities and mirrored rather than overlapping plots. This makes it possible to make the popular mirrored histogram plot for propensity scores. In addition, it’s now easier to change the colors of the components of the plots.
Made behavior around binary variables with interactions more like documentation, where interactions with both levels of the variable are present (thanks to @victorn1). Also, replaced _ with * as the delimiter between variable names in interactions. For the old behavior, use the “secret” option int_sep = "_" in bal.tab. This functionality is not documented (mostly because I’m lazy).
Expanded the flexibility of var.names in love.plot so that replacing the name of a variable will replace it everywhere it appears, including interactions. Thanks to @victorn1 for the suggestion.
Added var.names function to extract and save variable names from bal.tab objects. This makes it a lot easier to create replacement names for use in love.plot. Thanks to @victorn1 for the suggestion.
When weighted correlations are computed for continuous treatments, the denominator of the correlation now uses the unweighted standard deviations. See ?bal.tab for the rationale.
Version 3.3.0
Added methods for objects from the designmatch package.
Added methods for ps.cont objects from the WeightIt package.
Fixed bugs resulting form changes to how formula inputs are handled.
Cleaned up some internal functions, also fixing some related bugs
Added subset option in all bal.tab() methods (and consequently in bal.plot()) that allows users to specify a subset of the data to assess balance on (i.e., instead of the whole data set). This provides a workaround for methods were the cluster option isn’t allowed (e.g., longitudinal treatments) but balance is desired on subsets of the data. However, in most cases, cluster with which.cluster specified makes more sense.
Updated help files, in particular, more clearly documenting methods for iptw objects from twang and CBMSM objects from CBPS.
Added pretty printing with crayon, inspired by Jacob Long’s jtools package
Added abs option to bal.tab to display absolute values of statistics, which can be especially helpful for aggregated output. This also affects how love.plot() handles aggregated balance statistics.
Version 3.2.3
Added support for data with missing covariates. bal.tab() will produce balanace statistics for the non-missing values and will automatically create a new variable indicating whether the variable is missing or not and produce balance statistics on this variable as well.
Fixed a bug when displaying maximum imbalances with subclassification.
Fixed a bug where the unadjusted statistics were not displayed when using love.plot() with subclasses. (Thanks to Megha Joshi.)
Add the ability to display individual subclass balance using love.plot() with subclasses.
Under-the-hood changes to how weightit objects are handled.
Objects in the environment are now handled better by bal.tab() with the formula interface. The data argument is now optional if all variables in the formula exist in the environment.
Version 3.2.2
Fixed a bug when using get.w() (and bal.tab()) with mnps objects from twang with only one stop method.
Fixed a bug when using bal.tab() with twang objects that contained missing covariate values.
Fixed a bug when using int = TRUE in bal.tab() with few covariates.
Fixed a bug when variable names had special characters.
Added ablity to check higher order polynomials by setting int to a number.
Changed behavior of bal.tab() with multinomial treatments and s.d.denom = "pooled" to use the pooled standard deviation from the entire sample, not just the paired treatments.
Restored some vignettes that required WeightIt.
Version 3.2.1
Edits to vignettes and help files to respond to missing packages. Some vignette items may not display if packages are (temporarily) unavailable.
Fixed issue with sampling weights in CBPS objects. (Thanks to @kkranker on Github.)
Added more support for sampling weights in get.w() and help files.
Version 3.2.0
Added support for longitudinal treatments in bal.tab(), bal.plot(), and love.plot(), including output from iptw() in twang, CBMSM() from CBPS, and weightitMSM() from WeightIt.
Added a vignette to explain use with longitudinal treatments.
Edits to help files.
Added ability to change density options in bal.plot().
Added support for imp in bal.tab() for weightit objects.
Fixed bugs when limited variables were present. (One found and fixed by @sumtxt on Github.)
Fixed bug with multiple methods when weights were entered as a list.
Version 3.1.0
Added full support for tibbles.
Examples for weightit methods in documentation and vignette now work.
Improved speed and performance.
Added pairwise option for bal.tab() with multinomial treatments.
Increased flexibility for displaying balance using love.plot() with clustered or multiply imputed data.
Added imbalanced.only and disp.bal.tab options to bal.tab().
Fixes to the vignettes. Also, creation of a new vignette to simplify the main one.
Version 3.0.0
Added support for multinomial treatments in bal.tab(), including output from CBPS and twang.
Added support for weightit objects from WeightIt, including for multinomial treatments.
Added support for ebalance.trim objects from ebal.
Fixes to the vignette.
Fixes to splitfactor() to handle tibbles better.
Fixed bug when using bal.tab() with multiply imputed data without adjustment. Fixed bug when using s.weights with the formula method of bal.tab().
Version 2.2.0
Added disp.ks and ks.threshold options to bal.tab() to display Kolmogorov-Smirnov statistics before and after preprocessing.
Added support for sampling weights, which are applied to both control and treated units, using option s.weights in bal.tab(). Sampling weights are also now compatible with the sampling weights in ps objects from twang; the default is to apply the sampling weights before and after adjustment, mimicking the behavior of bal.table() in twang.
Changed behavior of bal.tab() for ps objects to allow displaying balance for more than one stop method at a time, and to default to displaying balance for all available stop methods. The full.stop.method argument in bal.tab() has been renamed stop.method, but full.stop.method still works. get.w() for ps objects has also gone through some changes to be more like twang’s get.weights().
Added support in bal.tab() and bal.plot() for subclassification with continuous treatments.
Added support in splitfactor() and unsplitfactor() for NA values
Fixed a bug in love.plot() caused when var.order was specified to be a sample that was not present.
Version 2.1.0
Added support in bal.tab(), bal.plot(), and love.plot() for examining balance on multiple weight specifications at a time
Added new utilities splitfactor(), unsplitfactor(), and get.w()
Added option in bal.plot() to display points sized by weights when treatment and covariate are continuous
Added which = "both" option in bal.plot() to simultaneously display plots for both adjusted and unadjusted samples; changed argument syntax to accommodate
Allowed bal.plot() to display balance for mutliple clusters and imputations simultaneously
Allowed bal.plot() to display balance for mutliple subclasses simultaneously with which.sub
Fixes to love.plot() to ensure adjusted points are in front of unadjusted points; changed colors and shape defaults and allowable values
Fixed bug where s.d.denom and estimand were not functioning correctly in bal.tab()
distance, addl, and weights can now be specified as lists of the usual arguments
Version 2.0.0
Added support for matching using the optmatch package or by specifying matching strata.
Added full support (bal.tab(), love.plot(), and bal.plot()) for multiply imputed data, including for clustered data sets.
Added support for multiple distance measures, including special treatment in love.plot()
Adjusted specifications in love.plot() for color and shape of points, and added option to generate a line connecting the points.
Adjusted love.plot() display to perform better on Windows.
Added capabilties for love.plot() and bal.plot() to display plots for multiple groups at a time
Added flexibility to f.build().
Updated bal.plot(), giving the capability to view multiple plots for subclassified or clustered data. Multinomial treatments are also supported.
Created a new vignette for clustered and multiply imputed data
Speed improvements
Fixed a bug causing mislabelling of categorical variables
Changed calculation of weighted variance to be in line with recommendations; CBPS can now be used with standardized weights
Version 1.3.1
Added support for entropy balancing through the ebal package.
Changed default color scheme of love.plot() to be black and white and added options for color, shape, and size of points.
Added sample size calculations for continuous treatments.
Edits to the vignette.
Version 1.3.0
Increased capabilities for cluster balance in bal.tab() and love.plot()
Increased information and decreased redundancy when assessing balance on interactions
Added quick option for bal.tab() to increase speed
Added options for print()
Bug fixes
Speed improvements
Edits to the vignette
Version 1.2.0
Added support for continuous treatment variables in bal.tab(), bal.plot(), and love.plot()
Added balance assessment within and across clusters
Other small performance changes to minimize errors and be more intuitive
Major revisions and adjustments to the vignette
Version 1.1.0
Added a vignette.
Fixed error in bal.tab.Match that caused wrong values and and warning messages when used.
Added new capabilities to bal.plot, including the ability to view unadjusted sample distributions, categorical variables as such, and the distance measure. Also updated documentation to reflect these changes and make which.sub more focal.
Allowed subclasses to be different from simply 1:S by treating them like factors once input is numerical
Changed column names in Balance table output to fit more compactly, and updated documentation to reflect these changes.
Other small performance changes to minimize errors and be more intuitive.