version 4.0.0

DESCRIPTION

@@ -1,22 +1,27 @@
 Package: cobalt
 Title: Covariate Balance Tables and Plots
-Version: 3.9.0
-Author: Noah Greifer [aut, cre]
-Maintainer: Noah Greifer <noah.greifer@gmail.com>
+Version: 4.0.0
+Authors@R: c(
+    person("Noah", "Greifer", role=c("aut", "cre"), 
+           email = "noah.greifer@gmail.com",
+	       comment=c(ORCID="0000-0003-3067-7154"))
+    )
 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.
 Depends: R (>= 3.3.0)
 Imports: ggplot2 (>= 3.0.0), grid, gtable (>= 0.3.0), gridExtra (>=
-        2.3.0), ggstance, crayon, backports (>= 1.1.1)
+        2.3.0), ggstance, crayon, backports (>= 1.1.5)
 Suggests: MatchIt, WeightIt (>= 0.5.0), twang, Matching, optmatch,
-        ebal, CBPS (>= 0.17), designmatch, optweight, mice, mlogit (>=
-        0.3-0), knitr, rmarkdown
+        ebal, CBPS (>= 0.17), designmatch, optweight, mice, MatchThem,
+        mlogit (>= 0.3-0), knitr, rmarkdown
 License: GPL (>= 2)
 Encoding: UTF-8
 LazyData: true
 VignetteBuilder: knitr
 URL: https://github.com/ngreifer/cobalt
 BugReports: https://github.com/ngreifer/cobalt/issues
 NeedsCompilation: no
-Packaged: 2019-10-06 18:40:11 UTC; NoahGreifer
+Packaged: 2020-01-08 03:08:29 UTC; NoahGreifer
+Author: Noah Greifer [aut, cre] (<https://orcid.org/0000-0003-3067-7154>)
+Maintainer: Noah Greifer <noah.greifer@gmail.com>
 Repository: CRAN
-Date/Publication: 2019-10-06 19:10:02 UTC
+Date/Publication: 2020-01-08 14:20:10 UTC

MD5

@@ -1,70 +1,72 @@
-b51e255115ee664125148c3a67ea0823 *DESCRIPTION
-a4d777a34d4a7475163c98a96efe4787 *NAMESPACE
-a72572f93d30594ec46608f818b45ca4 *NEWS.md
-84d8739c383623a69e12736ebb7164a7 *R/SHARED.R
-c54949539a75ebd9aa11a2cd42a0d7d1 *R/bal.plot.R
-c8ce24b2fd5a38f24c860bb6cba557ce *R/bal.sum.R
-1f3c8024c92fa50441999dcd24ae620b *R/bal.tab.R
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-21900befd94df68c01f3e9c54bde4335 *R/functions_for_processing.R
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-97e9cbf360fcaf9871804058454dc688 *R/internal_utilities.R
-c198a302958d557571ee6ed5040d37be *R/love.plot.R
-4aa8feabdaf148577f465471281dfb73 *R/print.bal.tab.R
-45f6373c3f99b21a2766d90265d801a4 *R/utilities.R
-93e3353db8fdfeddee005661a1376cd2 *R/x2base.R
-502b8f122d8c64e2686b05fa95e730c3 *README.md
-1e4395c3da3ab30d2af5487e314a3108 *build/partial.rdb
-ae18eee1c8e1ea76ca7c2874a7a0f0ee *build/vignette.rds
+47eefd30a05192c6b5fc89c437bfb2e6 *DESCRIPTION
+2cd581487629ee17e079dc4c67c60234 *NAMESPACE
+f5779ef6a8fdeae28b8a7530be9454d7 *NEWS.md
+dff8043d16fbadfc524185010b2115b7 *R/SHARED.R
+f4f2a3e7b4fe92218cabed3f799af418 *R/bal.plot.R
+0ba22c78d842939a9b679280dc7c77ff *R/bal.sum.R
+f3e7ed03d8d3a2b8def861addf29d6ff *R/bal.tab.R
+e0ee6bcf38e1e880959347cd5e823876 *R/base.bal.tab.R
+6f2711d434ed72b688575022c3f87784 *R/functions_for_processing.R
+04d8924685731c8326b5fc2e5d94e714 *R/get.w.R
+847dd354006a4c576938187e635326b1 *R/internal_utilities.R
+85ed823dc342d1fc77d1d264fd62c9b3 *R/love.plot.R
+b693faa6fe84babe879f6f74e551783e *R/print.bal.tab.R
+b9de828b2e2baa51b5bbbecbe02c19c7 *R/utilities.R
+558a2a0becca4c703a37686573e7d67a *R/x2base.R
+31628b549eec9b002c58fbbac9816c4c *README.md
+0911d5f27416214ef9a9a9d015cf4224 *build/partial.rdb
+e5d8546f0554eec4bfe8dfec3f6c29f1 *build/vignette.rds
 949b492287de79b9a90d520db98768c1 *data/lalonde.RData
 d22e5afa667cdc190e348ae984c830a2 *data/lalonde_mis.RData
-a2492c0d8d9712ae761d70d074150c31 *inst/doc/cobalt_A0_basic_use.R
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-e7e14ebae827f86f1ad39c2b4d576410 *man/bal.plot.Rd
-a25b1608bbb704a4c20cb78e8a500035 *man/bal.tab.CBPS.Rd
-a621f3c2f5e174d86f5b0338eb7796d3 *man/bal.tab.Match.Rd
-2bdcbdea647019a22d690d1c33ca9ee7 *man/bal.tab.Rd
-51174518330ade0219059f8c2fbe6436 *man/bal.tab.default.Rd
-b9c6c887617cd15ef9e6a5cfdcb9f5c0 *man/bal.tab.df.formula.Rd
-68c91eb85591a65eda1234a208f4ca4d *man/bal.tab.df.formula.list.Rd
-f5e365856ed5fb53123f9c07280c4b03 *man/bal.tab.matchit.Rd
-15f7d88d16cede16ef5f55302981d0a3 *man/bal.tab.ps.Rd
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-33f8b0bf4f1923c488a09939c13acfd4 *man/class-bal.tab.imp.Rd
-1ad72e1e4ae6218dce6b6e36ecf3745f *man/class-bal.tab.msm.Rd
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+ca9c405904d25dd5fe0cba943de1ae2a *man/bal.tab.mimids.Rd
+56646d952aed383e98355ac575f06b15 *man/bal.tab.ps.Rd
+a096a91e8c5e5f27ebb0ee5bcf8f2198 *man/bal.tab.weightit.Rd
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+0e04f597a4ecce9718b50273744754b8 *man/class-bal.tab.imp.Rd
+315b524a7df2ceb331e1aa41a9ee147c *man/class-bal.tab.msm.Rd
+821720247ef6f0b29dbbbece3742cdc9 *man/class-bal.tab.multi.Rd
+ee72c079c1ab65b18c0d1e9407e0ebeb *man/class-bal.tab.subclass.Rd
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 caef175070abae4758aadce5074fcd2e *man/f.build.Rd
-73268c8d3169501e0a6b503cf31c9df5 *man/get.w.Rd
+40423f2a8a120ad7708ad1e7b06418bb *man/get.w.Rd
 967ae0375d22a6d36eb1b56b36907344 *man/lalonde.Rd
-5b4255e9d1e5d94ad96adc716b8ce13a *man/love.plot.Rd
-d90422bdb2a3cd144311f2b17166710b *man/print.bal.tab.Rd
+1c4689d7048432e428fd36ea731aa512 *man/love.plot.Rd
+1dec7076c9082290d886ef8b8a768e96 *man/print.bal.tab.Rd
 4ebf3f7cb697fadd5d356b8d4d27720d *man/set.cobalt.options.Rd
-ece3fdbbc7e4ed2ca03b622c22b0cf84 *man/splitfactor.Rd
-05a7e465db294a53fcc2eeddf8df06d3 *man/var.names.Rd
-c30ec1c5b1a8f6321544cd0eb58c9234 *vignettes/cobalt_A0_basic_use.Rmd
-9d90692ada3d40403c2b5c084b5ac9f3 *vignettes/cobalt_A1_other_packages.Rmd
-351641b376b05f177daeca68bde0a677 *vignettes/cobalt_A2_cluster_imp.Rmd
-e7f0e422126acc5e28e6a6d44d8e8e0a *vignettes/cobalt_A3_longitudinal_treat.Rmd
-b2bd7809f9c62cfd6fc4e0d9b28b6ade *vignettes/cobalt_A4_love.plot.Rmd
+5c04f697adb66b929435930ab332b164 *man/splitfactor.Rd
+ddcbaa39451e12585f33774522765190 *man/var.names.Rd
+c2944930a949ff9e00122a7a2027311b *vignettes/cobalt_A0_basic_use.Rmd
+1eaef187d3aedbebfb81891dd1f44261 *vignettes/cobalt_A1_other_packages.Rmd
+406b58a76c7fa6ba2910527ee7f45baf *vignettes/cobalt_A2_segmented_data.Rmd
+133a4a0585da5ea90c7815be489019f8 *vignettes/cobalt_A3_longitudinal_treat.Rmd
+7fa6ce962915c253e64f3a28fc9fd6e6 *vignettes/cobalt_A4_love.plot.Rmd

NAMESPACE

@@ -12,12 +12,12 @@ importFrom("ggstance", "position_dodgev")
 export(bal.tab, bal.plot, love.plot, f.build, splitfactor, 
        unsplitfactor, get.w, var.names, set.cobalt.options,
        get.cobalt.options,
-       col_w_mean, col_w_sd, col_w_smd, col_w_vr, col_w_ks, col_w_ovl, col_w_corr)
+       col_w_mean, col_w_sd, col_w_smd, col_w_vr, col_w_ks, col_w_ovl, 
+       col_w_cov, col_w_corr)
 S3method(print, bal.tab)
 S3method(print, bal.tab.subclass)
 S3method(print, bal.tab.cluster)
 S3method(print, bal.tab.imp)
-S3method(print, bal.tab.imp.cluster)
 S3method(print, bal.tab.multi)
 S3method(print, bal.tab.msm)
 S3method(plot, bal.tab)
@@ -39,8 +39,8 @@ S3method(bal.tab, ebalance.trim)
 S3method(bal.tab, optmatch)
 S3method(bal.tab, weightit)
 S3method(bal.tab, designmatch)
-#S3method(bal.tab, mimids)
-#S3method(bal.tab, wimids)
+S3method(bal.tab, mimids)
+S3method(bal.tab, wimids)
 S3method(bal.tab, formula.list)
 S3method(bal.tab, data.frame.list)
 S3method(bal.tab, CBMSM)
@@ -58,6 +58,6 @@ S3method(get.w, ebalance.trim)
 S3method(get.w, optmatch)
 S3method(get.w, weightit)
 S3method(get.w, designmatch)
-#S3method(get.w, mimids)
-#S3method(get.w, wimids)
+S3method(get.w, mimids)
+S3method(get.w, wimids)
 S3method(get.w, CBMSM)