version 3.4.1

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: cobalt
 Title: Covariate Balance Tables and Plots
-Version: 3.4.0
+Version: 3.4.1
 Author: Noah Greifer [aut, cre]
 Maintainer: Noah Greifer <noah.greifer@gmail.com>
 Description: Generate balance tables and plots for covariates of groups preprocessed through matching, weighting or subclassification, for example, using propensity scores. Includes integration with 'MatchIt', 'twang', 'Matching', 'optmatch', 'CBPS', 'ebal', 'WeightIt', and 'designmatch' for assessing balance on the output of their preprocessing functions. Users can also specify data for balance assessment not generated through the above packages. Also included are methods for assessing balance in clustered or multiply imputed data sets or data sets with longitudinal treatments.
@@ -11,12 +11,11 @@ Suggests: MatchIt, WeightIt (>= 0.3.0), twang, Matching, optmatch,
 License: GPL (>= 2)
 Encoding: UTF-8
 LazyData: true
-Date: 2018-08-12
 VignetteBuilder: knitr
 URL: https://github.com/ngreifer/cobalt
 BugReports: https://github.com/ngreifer/cobalt/issues
 RoxygenNote: 6.0.1
 NeedsCompilation: no
-Packaged: 2018-08-13 16:57:36 UTC; NoahGreifer
+Packaged: 2018-09-14 21:44:48 UTC; NoahGreifer
 Repository: CRAN
-Date/Publication: 2018-08-14 04:20:07 UTC
+Date/Publication: 2018-09-15 07:20:02 UTC

MD5

@@ -1,30 +1,30 @@
-533db5bdeb0d7f9914102e05d4f2d9d4 *DESCRIPTION
+27716d003ba1c832ad0c5495167e54ef *DESCRIPTION
 8c75818892d88aadbbe83600d5684433 *NAMESPACE
-98827f0b211b89f97c0c65fb0593bae9 *NEWS.md
-d902dd594c5f1bab61455586c47bce6a *R/bal.plot.R
-e5b9cc4fd07f2abc44b05a0d40fb846e *R/bal.tab.R
-778b2d197ae618b70e0db90e662e4c5c *R/functions_for_processing.R
+5734eb96fa85a4877655b520c63787e8 *NEWS.md
+2a7afa56a30528f58a3be3506bb10eec *R/bal.plot.R
+86a034282be87063cc70feaa6607bb20 *R/bal.tab.R
+252f00c539c595b16ee0938a76f896cb *R/functions_for_processing.R
 111c6a2e0a2855dddb82c83cbbfd8a4a *R/love.plot.R
-d6a0599bb4656e35823f7fc5e596d7ae *R/print.bal.tab.R
-3e312a8646fcdc606cc5bfaf2b91a863 *R/utilities.R
-0069a58c5341c762a8f1a6f113ca0359 *R/x2base.R
+1cd1d7409f193af8312ff0fa39d960c2 *R/print.bal.tab.R
+24d0ea8c0ffb311c6b93aaace001e9de *R/utilities.R
+6ed2b9aa25ffdce5485064ee239d8b06 *R/x2base.R
 0230929ebe6a272d2311fcb946c97905 *README.md
-7c338a77747e25ff93f0ddd4a7ac32c2 *build/partial.rdb
+b5884e50d0bccdd21a693827846a5b07 *build/partial.rdb
 a68a3a523252ed2db3875ef7f896471a *build/vignette.rds
 949b492287de79b9a90d520db98768c1 *data/lalonde.RData
 d22e5afa667cdc190e348ae984c830a2 *data/lalonde_mis.RData
 ac2fe583baedeb21fb9ee6b150a3b1be *inst/doc/cobalt_A0_basic_use.R
-e96cf4b6e3d73ddb02b76015e9b4dc82 *inst/doc/cobalt_A0_basic_use.Rmd
-55f4db95f468a74dc23096b7ae5d8093 *inst/doc/cobalt_A0_basic_use.html
+99c19c1af0dcbf3e284b05847a5cc0fb *inst/doc/cobalt_A0_basic_use.Rmd
+c05df2da2707ec076d993cab2cb2da0f *inst/doc/cobalt_A0_basic_use.html
 e767c6ba0dc0e71cc6ff9f796f072eeb *inst/doc/cobalt_A1_other_packages.R
 595fcd32fc888e345d5e67efde1c2dbd *inst/doc/cobalt_A1_other_packages.Rmd
-e1f756bac0217363606087000b3acd3c *inst/doc/cobalt_A1_other_packages.html
+3cc4b286972ee52d62e019824b5efabb *inst/doc/cobalt_A1_other_packages.html
 1e55dd7772ee036af5b6c1396441f22e *inst/doc/cobalt_A2_cluster_imp.R
 b38661cc43d2f62eb39b4c0213e86072 *inst/doc/cobalt_A2_cluster_imp.Rmd
-0df946a683b4b5481c3ce31227e47eb0 *inst/doc/cobalt_A2_cluster_imp.html
+c8cd44e4816aba3878c0bac23eab91c2 *inst/doc/cobalt_A2_cluster_imp.html
 8c429299d3a0b9e1d5b61fd3cf3d2d58 *inst/doc/cobalt_A3_longitudinal_treat.R
 f88d8c92fbc7efa42ea3d78ea86c7fa3 *inst/doc/cobalt_A3_longitudinal_treat.Rmd
-e450d82bc548895d3c04435c7e9e6eda *inst/doc/cobalt_A3_longitudinal_treat.html
+89c91cc12d9bc70d86d02574f99bde26 *inst/doc/cobalt_A3_longitudinal_treat.html
 324de8fe4c2c8ce07434ae41b018702f *inst/figures/README-unnamed-chunk-3-1.png
 5337340e8d5bbd86e9fa43c6ec979374 *inst/figures/README-unnamed-chunk-3-2.png
 797f8b0a88cb066430299b3ae748efa8 *inst/figures/README-unnamed-chunk-3-3.png
@@ -39,7 +39,7 @@ df088bd45c3d27a6c67789e2cb5e91be *man/bal.tab.Match.Rd
 2de1cc4f94dc2e9ae09a3693dff1adba *man/bal.tab.ebalance.Rd
 441501808092f72f6ba00e7567651ad3 *man/bal.tab.matchit.Rd
 91e4418dfdb66884c5ae00735a3ba1d9 *man/bal.tab.optmatch.Rd
-889b7bf958ee43c68ea4cd6f3ec91df0 *man/bal.tab.ps.Rd
+999ee9c279c23a259faaaca37c8b9efe *man/bal.tab.ps.Rd
 14a510451ff0acad0ee8d470adc12040 *man/bal.tab.time.list.Rd
 8e89806bcdc2a23bd3c7b8829f8aee0c *man/bal.tab.weightit.Rd
 5393b869fd5241a0b67a953d0bfd50eb *man/class-bal.tab.cluster.Rd
@@ -52,9 +52,9 @@ a08ee89605f037da64ad5c71d24badec *man/f.build.Rd
 e43b36b1df7ae5954e88f78eeb9d7f87 *man/lalonde.Rd
 fc26c4cd0a640103df0cac2cff089acb *man/love.plot.Rd
 d0d0bd8d571d0607a4066347fb32620c *man/print.bal.tab.Rd
-969532fe9e9ee03bfb532d4255a2f49b *man/splitfactor.Rd
+4650b55c6932be5377877a1fa960cb6e *man/splitfactor.Rd
 886f4a717e9a135f5f58ddc1db2e8dee *man/var.names.Rd
-e96cf4b6e3d73ddb02b76015e9b4dc82 *vignettes/cobalt_A0_basic_use.Rmd
+99c19c1af0dcbf3e284b05847a5cc0fb *vignettes/cobalt_A0_basic_use.Rmd
 595fcd32fc888e345d5e67efde1c2dbd *vignettes/cobalt_A1_other_packages.Rmd
 b38661cc43d2f62eb39b4c0213e86072 *vignettes/cobalt_A2_cluster_imp.Rmd
 f88d8c92fbc7efa42ea3d78ea86c7fa3 *vignettes/cobalt_A3_longitudinal_treat.Rmd

NEWS.md

@@ -1,6 +1,24 @@
 cobalt News and Updates
 ======
 
+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 :)
@@ -17,7 +35,7 @@ Version 3.4.0
 
 * 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 uses the unweighted standard deviations. See `?bal.tab` for the rationale.
+* 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
 
@@ -31,7 +49,7 @@ Version 3.3.0
 
 * 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 particularly more clearly documenting methods for `iptw` objects from `twang` and `CBMSM` objects from `CBPS`.
+* 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
 

R/bal.plot.R

@@ -28,7 +28,7 @@ bal.plot <- function(obj, var.name, ..., which, which.sub = NULL, cluster = NULL
         }
         if (all(sapply(var.list, is_null))) stop(paste0("\"", var.name, "\" is not the name of a variable in any available data set input."), call. = FALSE)
         X$var <- unlist(var.list[appears.in.time])
-        X$time <- rep(seq_along(X$covs.list)[appears.in.time], each = nrow(X$covs.list[[1]]))
+        X$time <- rep(seq_along(X$covs.list)[appears.in.time], each = NROW(X$covs.list[[1]]))
         X$treat <- unlist(X$treat.list[appears.in.time])
         if (is_not_null(names(X$treat.list))) treat.names <- names(X$treat.list)
         else treat.names <- seq_along(X$treat.list)
@@ -93,7 +93,7 @@ bal.plot <- function(obj, var.name, ..., which, which.sub = NULL, cluster = NULL
                 in.sub <- !is.na(X$subclass) & X$subclass %in% which.sub
                 D <- setNames(as.data.frame(matrix(0, nrow = sum(in.sub), ncol = 4)),
                               c("weights", "treat", "var", "subclass"))
-                D$weights <- rep(1, nrow(D))
+                D$weights <- rep(1, NROW(D))
                 D$treat <- X$treat[in.sub]
                 D$var <- X$var[in.sub]
                 D$subclass <- paste("Subclass", X$subclass[in.sub])
@@ -107,7 +107,7 @@ bal.plot <- function(obj, var.name, ..., which, which.sub = NULL, cluster = NULL
         if (which == "both") {
             D2 <- setNames(as.data.frame(matrix(0, nrow = length(X$treat), ncol = 4)),
                            c("weights", "treat", "var", "subclass"))
-            D2$weights <- rep(1, nrow(D2))
+            D2$weights <- rep(1, NROW(D2))
             D2$treat <- X$treat
             D2$var <- X$var
             D2$subclass <- rep("Unadjusted Sample", length(X$treat))
@@ -308,7 +308,7 @@ bal.plot <- function(obj, var.name, ..., which, which.sub = NULL, cluster = NULL
 
         if (is.categorical.var) { #Categorical vars
             d$var <- factor(d$var)
-            cat.sizes <- tapply(rep(1, nrow(d)), d$var, sum)
+            cat.sizes <- tapply(rep(1, NROW(d)), d$var, sum)
             smallest.cat <- names(cat.sizes)[which.min(cat.sizes)]
             if (is.character(bw)) {
                 if (is.function(get0(paste0("bw.", bw)))) {
@@ -436,7 +436,7 @@ bal.plot <- function(obj, var.name, ..., which, which.sub = NULL, cluster = NULL
                 geom_hline(yintercept = 0)
         }
         else { #Continuous vars
-            t.sizes <- tapply(rep(1, nrow(d)), d$treat, sum)
+            t.sizes <- tapply(rep(1, NROW(d)), d$treat, sum)
             smallest.t <- names(t.sizes)[which.min(t.sizes)]
             if (is.character(bw)) {
                 if (is.function(get0(paste0("bw.", bw)))) {