bal.tab.weightit {cobalt} | R Documentation |
Balance Statistics for WeightIt
Objects
Description
Generates balance statistics for weightit
and weightitMSM
objects from WeightIt.
Usage
## S3 method for class 'weightit'
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 |
a |
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 |
|
... |
for some input types, other arguments that are required or allowed. Otherwise, further arguments to control display of output. See display options for details. |
Details
bal.tab.weightit()
generates a list of balance summaries for the weightit
object given.
Value
For point treatments, if clusters and imputations are not specified, an object of class "bal.tab"
containing balance summaries for the weightit
object. See bal.tab()
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. See class-bal.tab.imp
for details.
If weightit()
is used with multi-category treatments, an object of class "bal.tab.multi"
containing balance summaries for each pairwise treatment comparison. See bal.tab.multi()
for details.
If weightitMSM()
is used for longitudinal treatments, an object of class "bal.tab.msm"
containing balance summaries for each time period. See class-bal.tab.msm
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.
See Also
-
bal.tab()
for details of calculations.
Examples
library(WeightIt)
data("lalonde", package = "cobalt")
## Basic propensity score weighting
w.out1 <- weightit(treat ~ age + educ + race +
married + nodegree + re74 + re75,
data = lalonde, method = "glm")
bal.tab(w.out1, un = TRUE, m.threshold = .1,
v.threshold = 2)
## Weighting with a multi-category treatment
w.out2 <- weightit(race ~ age + educ + married +
nodegree + re74 + re75,
data = lalonde, method = "glm",
estimand = "ATE")
bal.tab(w.out2, un = TRUE)
bal.tab(w.out2, un = TRUE, pairwise = FALSE)
## IPW for longitudinal treatments
data("msmdata", package = "WeightIt")
wmsm.out <- weightitMSM(list(A_1 ~ X1_0 + X2_0,
A_2 ~ X1_1 + X2_1 +
A_1 + X1_0 + X2_0,
A_3 ~ X1_2 + X2_2 +
A_2 + X1_1 + X2_1 +
A_1 + X1_0 + X2_0),
data = msmdata,
method = "glm")
bal.tab(wmsm.out)