bal.tab.default {cobalt} | R Documentation |
Balance Statistics for Other Objects
Description
Generates balance statistics using an object for which there is not a defined method.
Usage
## Default S3 method:
bal.tab(
x,
stats,
int = FALSE,
poly = 1,
distance = NULL,
addl = NULL,
data = 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,
...
)
Arguments
x |
An object containing information about conditioning. 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, |
data |
an optional data frame containing variables named in other arguments. For some input object types, this is required. |
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 |
|
... |
other arguments that would be passed to |
Details
bal.tab.default()
processes its input and attempt to extract enough information from it to display covariate balance for x
. The purpose of this method is to allow users who have created their own objects containing conditioning information (i.e., weights, subclasses, treatments, covariates, etc.) to access the capabilities of bal.tab()
without having a special method written for them. By including the correct items in x
, bal.tab.default()
can present balance tables as if the input was the output of one of the specifically supported packages (e.g., MatchIt, twang, etc.).
The function will search x
for the following named items and attempt to process them:
treat
A vector (
numeric
,character
,factor
) containing the values of the treatment for each unit or the name of the column indata
containing them. Essentially the same input totreat
inbal.tab.data.frame()
.treat.list
A list of vectors (
numeric
,character
,factor
) containing, for each time point, the values of the treatment for each unit or the name of the column indata
containing them. Essentially the same input totreat.list
inbal.tab.time.list()
.covs
A
data.frame
containing the values of the covariates for each unit. Essentially the same input tocovs
inbal.tab.data.frame()
.covs.list
A list of
data.frame
s containing, for each time point, the values of the covariates for each unit. Essentially the same input tocovs.list
inbal.tab.time.list()
.formula
A
formula
with the treatment variable as the response and the covariates for which balance is to be assessed as the terms. Essentially the same input toformula
inbal.tab.formula()
.formula.list
A list of
formula
s with, for each time point, the treatment variable as the response and the covariates for which balance is to be assessed as the terms. Essentially the same input toformula.list
inbal.tab.time.list()
.data
A
data.frame
containing variables with the names used in other arguments and components (e.g.,formula
,weights
, etc.). Essentially the same input todata
inbal.tab.formula()
,bal.tab.data.frame()
, orbal.tab.time.list()
.weights
A vector, list, or
data.frame
containing weights for each unit or a string containing the names of the weights variables indata
. Essentially the same input toweights
inbal.tab.data.frame()
orbal.tab.time.list()
.distance
-
A vector, 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,
bal.tab()
will look in the argument todata
, if specified. Essentially the same input todistance
inbal.tab.data.frame()
. formula.list
A list of vectors or
data.frame
s containing, for each time point, distance values (e.g., propensity scores) for each unit or a string containing the name of the distance variable indata
. Essentially the same input todistance.list
inbal.tab.time.list()
.subclass
A vector containing subclass membership for each unit or a string containing the name of the subclass variable in
data
. Essentially the same input tosubclass
inbal.tab.data.frame()
.match.strata
A vector containing matching stratum membership for each unit or a string containing the name of the matching stratum variable in
data
. Essentially the same input tomatch.strata
inbal.tab.data.frame()
.estimand
A
character
vector; whether the desired estimand is the "ATT", "ATC", or "ATE" for each set of weights. Essentially the same input toestimand
inbal.tab.data.frame()
.s.weights
A vector containing sampling weights for each unit or a string containing the name of the sampling weight variable in
data
. Essentially the same input tos.weights
inbal.tab.data.frame()
orbal.tab.time.list()
.focal
The name of the focal treatment when multi-category treatments are used. Essentially the same input to
focal
inbal.tab.data.frame()
.call
A
call
object containing the function call, usually generated by usingmatch.call()
inside the function that createdx
.
Any of these items can also be supplied directly to bal.tab.default
, e.g., bal.tab.default(x, formula = treat ~ x1 + x2)
. If supplied, it will override the object with the same role in x
. In addition, any arguments to bal.tab.formula()
, bal.tab.data.frame()
, and bal.tab.time.list()
are allowed and perform the same function.
At least some inputs containing information to create the treatment and covariates are required (e.g., formula
and data
or covs
and treat
). All other arguments are optional and have the same defaults as those in bal.tab.data.frame()
or bal.tab.time.list()
. If treat.list
, covs.list
, or formula.list
are supplied in x
or as an argument to bal.tab.default()
, the function will proceed considering a longitudinal treatment. Otherwise, it will proceed considering a point treatment.
bal.tab.default()
, like other bal.tab()
methods, is just a shortcut to supply arguments to bal.tab.data.frame()
or bal.tab.time.list()
. Therefore, any matters regarding argument priority or function are described in the documentation for these methods.
Value
For point treatments, if clusters and imputations are not specified, an object of class "bal.tab"
containing balance summaries for the specified treatment and covariates. 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.
If imputations are specified, an object of class "bal.tab.imp"
containing balance summaries for each imputation and a summary of balance across imputations, just as with clusters. See class-bal.tab.imp
for details.
If multi-category treatments are used, an object of class "bal.tab.multi"
containing balance summaries for each pairwise treatment comparison and a summary of balance across pairwise comparisons. See bal.tab.multi()
for details.
If longitudinal treatments are used, an object of class "bal.tab.msm"
containing balance summaries at each time point. Each balance summary is its own bal.tab
object. See class-bal.tab.msm
for more details.
See Also
-
bal.tab.formula()
andbal.tab.time.list()
for additional arguments to be supplied. -
bal.tab()
for output and details of calculations. -
class-bal.tab.cluster
for more information on clustered data. -
class-bal.tab.imp
for more information on multiply imputed data. -
bal.tab.multi()
for more information on multi-category treatments.
Examples
data("lalonde", package = "cobalt")
covs <- subset(lalonde, select = -c(treat, re78))
##Writing a function the produces output for direct
##use in bal.tab.default
ate.weights <- function(treat, covs) {
data <- data.frame(treat, covs)
formula <- formula(data)
ps <- glm(formula, data = data,
family = "binomial")$fitted.values
weights <- treat/ps + (1-treat)/(1-ps)
call <- match.call()
out <- list(treat = treat,
covs = covs,
distance = ps,
weights = weights,
estimand = "ATE",
call = call)
return(out)
}
out <- ate.weights(lalonde$treat, covs)
bal.tab(out, un = TRUE)