bal.tab.designmatch | R Documentation |
designmatch
ObjectsGenerates balance statistics for output objects from designmatch.
## S3 method for class 'designmatch'
bal.tab(
x,
formula = NULL,
data = NULL,
treat = NULL,
covs = NULL,
stats,
int = FALSE,
poly = 1,
distance = NULL,
addl = NULL,
continuous,
binary,
s.d.denom,
thresholds = NULL,
weights = NULL,
cluster = NULL,
imp = NULL,
pairwise = TRUE,
s.weights = NULL,
abs = FALSE,
subset = NULL,
quick = TRUE,
...
)
x |
the output of a call to \pkgfundesignmatchbmatch or related wrapper functions from the designmatch package. |
formula |
a |
data |
a data frame containing variables named in |
treat |
a vector of treatment statuses. See Details. |
covs |
a data frame of covariate values for which to check balance. See Details. |
stats |
|
int |
|
poly |
|
distance |
an optional formula or data frame containing distance values (e.g., propensity scores) or a character vector containing their names. If a formula or variable names are specified, |
addl |
an optional formula or data frame containing additional covariates for which to present balance or a character vector containing their names. If a formula or variable names are specified, |
continuous |
whether mean differences for continuous variables should be standardized ( |
binary |
whether mean differences for binary variables (i.e., difference in proportion) should be standardized ( |
s.d.denom |
|
thresholds |
a named vector of balance thresholds, where the name corresponds to the statistic (i.e., in |
weights |
a vector, list, or |
cluster |
either a vector containing cluster membership for each unit or a string containing the name of the cluster membership variable in |
imp |
either a vector containing imputation indices for each unit or a string containing the name of the imputation index variable in |
pairwise |
whether balance should be computed for pairs of treatments or for each treatment against all groups combined. See |
s.weights |
Optional; either a vector containing sampling weights for each unit or a string containing the name of the sampling weight variable in |
abs |
|
subset |
a |
quick |
|
... |
for some input types, other arguments that are required or allowed. Otherwise, further arguments to control display of output. See display options for details. |
bal.tab()
generates a list of balance summaries for the object given, and functions similarly to \pkgfundesignmatchmeantab. Note that output objects from designmatch do not have their own class; bal.tab()
first checks whether the object meets the criteria to be treated as a designmatch
object before dispatching the correct method. Renaming or removing items from the output object can create unintended consequences.
The input to bal.tab.designmatch()
must include either both formula
and data
or both covs
and treat
. Using the covs
+ treat
input mirrors how \pkgfundesignmatchmeantab is used (note that to see identical results to meantab()
, s.d.denom
must be set to "pooled"
).
If clusters and imputations are not specified, an object of class "bal.tab"
containing balance summaries for the given object. See bal.tab()
for details.
If clusters are specified, an object of class "bal.tab.cluster"
containing balance summaries within each cluster and a summary of balance across clusters. See class-bal.tab.cluster
for details.
bal.tab()
for details of calculations.
data("lalonde", package = "cobalt")
library(designmatch)
covariates <- as.matrix(lalonde[c("age", "educ", "re74", "re75")])
treat <- lalonde$treat
dmout <- bmatch(treat,
total_groups = sum(treat == 1),
mom = list(covs = covariates,
tols = absstddif(covariates,
treat, .05))
)
## Using treat and covs
bal.tab(dmout, treat = treat, covs = covariates)
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