Fixed issue with tibble dataset, discard, and optimal/full matching (k…

…osukeimai#185)
ngreifer · Jan 19, 2024 · 947a0b8 · 947a0b8
1 parent f526eca
commit 947a0b8
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,5 +1,5 @@
 Package: MatchIt
-Version: 4.5.5
+Version: 4.5.5.9000
 Title: Nonparametric Preprocessing for Parametric Causal Inference
 Description: Selects matched samples of the original treated and
     control groups with similar covariate distributions -- can be

diff --git a/MatchIt.Rproj b/MatchIt.Rproj
@@ -18,3 +18,4 @@ BuildType: Package
 PackageUseDevtools: Yes
 PackageInstallArgs: --no-multiarch --with-keep.source
 PackageCheckArgs: --as-cran
+PackageRoxygenize: rd,collate,namespace
diff --git a/NEWS.md b/NEWS.md
@@ -6,6 +6,10 @@ output:
 `MatchIt` News and Updates
 ======
 
+# MatchIt (development version)
+
+* Fixed a bug when using `method = "optimal"` or `method = "full"` with `discard` specified and `data` given as a tibble (`tbl_df` object). (#185)
+
 # MatchIt 4.5.5
 
 * When using `method = "cardinality"`, a new solver, HiGHS, can be requested by setting `solver = "highs"`, which relies on the `highs` package. This is much faster and more reliable than GLPK and is free and easy to install as a regular R package with no additional requirements.

diff --git a/R/matchit2full.R b/R/matchit2full.R
@@ -303,7 +303,7 @@ matchit2full <- function(treat, formula, data, distance, discarded,
   mo <- mo[!discarded[treat == focal], !discarded[treat != focal], drop = FALSE]
   dimnames(mo) <- list(names(treat_)[treat_ == 1], names(treat_)[treat_ == 0])
 
-  mo <- optmatch::match_on(mo, data = data[!discarded,, drop = FALSE])
+  mo <- optmatch::match_on(mo, data = as.data.frame(data)[!discarded,, drop = FALSE])
   mo <- optmatch::as.InfinitySparseMatrix(mo)
 
   #Process antiexact

diff --git a/R/matchit2optimal.R b/R/matchit2optimal.R
@@ -244,7 +244,7 @@ matchit2optimal <- function(treat, formula, data, distance, discarded,
                             ratio = 1, s.weights = NULL, caliper = NULL,
                             mahvars = NULL, exact = NULL,
                             estimand = "ATT", verbose = FALSE,
-                            is.full.mahalanobis,  antiexact = NULL, ...) {
+                            is.full.mahalanobis, antiexact = NULL, ...) {
 
   rlang::check_installed("optmatch")
 
@@ -360,7 +360,7 @@ matchit2optimal <- function(treat, formula, data, distance, discarded,
   mo <- mo[!discarded[treat == focal], !discarded[treat != focal], drop = FALSE]
   dimnames(mo) <- list(names(treat_)[treat_ == 1], names(treat_)[treat_ == 0])
 
-  mo <- optmatch::match_on(mo, data = data[!discarded,, drop = FALSE])
+  mo <- optmatch::match_on(mo, data = as.data.frame(data)[!discarded,, drop = FALSE])
   mo <- optmatch::as.InfinitySparseMatrix(mo)
 
   #Process antiexact