Balance Statistics for twang Objects
Generates balance statistics for ps
, mnps
, and iptw
objects from twang and for ps.cont
objects from WeightIt.
## S3 method for class 'ps' bal.tab(x, stop.method, 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, abs = FALSE, subset = NULL, quick = TRUE, ...) ## S3 method for class 'mnps' bal.tab(x, stop.method, 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, abs = FALSE, subset = NULL, quick = TRUE, ...) ## S3 method for class 'iptw' bal.tab(x, stop.method, stats, int = FALSE, poly = 1, distance.list = NULL, addl.list = NULL, data = NULL, continuous, binary, s.d.denom, thresholds = NULL, weights = NULL, cluster = NULL, imp = NULL, pairwise = TRUE, abs = FALSE, subset = NULL, quick = TRUE, ...) ## S3 method for class 'ps.cont' bal.tab(x, stop.method, stats, int = FALSE, poly = 1, distance = NULL, addl = NULL, data = NULL, continuous, binary, s.d.denom, thresholds = NULL, weights = NULL, cluster = NULL, imp = NULL, abs = FALSE, subset = NULL, quick = TRUE, ...)
x |
a |
stop.method |
a string containing the names of the stopping methods used in the original call to |
stats |
|
int |
|
poly |
|
distance, distance.list |
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, addl.list |
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 that might be named in arguments to |
continuous |
whether mean differences for continuous covariates should be standardized ( |
binary |
whether mean differences for binary covariates (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 named list containing additional weights on which to assess balance. Each entry can be a vector of weights, the name of a variable in |
cluster |
either a vector containing cluster membership for each unit or a string containing the name of the cluster membership variable in data or the |
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 |
abs |
|
subset |
a |
quick |
|
... |
further arguments to control display of output. See display options for details. |
bal.tab.ps()
generates a list of balance summaries for the ps
object given, and functions similarly to twang::bal.table()
.
The threshold
argument controls whether extra columns should be inserted into the Balance table describing whether the balance statistics in question exceeded or were within the threshold. Including these thresholds also creates summary tables tallying the number of variables that exceeded and were within the threshold and displaying the variables with the greatest imbalance on that balance measure.
For binary point treatments, if clusters are not specified, an object of class "bal.tab"
containing balance summaries for the ps
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 bal.tab.cluster
for details.
If mnps()
is used with multi-category treatments, 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.
The function bal.table
in twang performs a similar function. The variances used in the denominator of the standardized mean difference are weighted and computed using survey::svyvar()
in twang and are unweighted here (except when s.weights
are specified, in which case col_w_sd
is used). twang also uses "all" as the default s.d.denom
when the estimand is the ATE; the default here is "pooled". For this reason, results may differ slightly between the two packages.
Noah Greifer
bal.tab()
for details of calculations.
bal.tab.cluster
for more information on clustered data.
bal.tab.multi
for more information on multi-category treatments.
bal.tab.msm
for more information on longitudinal treatments.
library(twang); data("lalonde", package = "cobalt") ## Using ps() for generalized boosted modeling ps.out <- ps(treat ~ age + educ + married + race + nodegree + re74 + re75, data = lalonde, stop.method = c("ks.mean", "es.mean"), estimand = "ATT", verbose = FALSE) bal.tab(ps.out, stop.method = "ks.mean", un = TRUE, m.threshold = .1, disp.ks = TRUE)
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.