Usage
PSAboot(Tr, Y, X, M = 100, formu = as.formula(paste0("treat ~ ",
paste0(names(X), collapse = " + "))), control.ratio = 5,
control.sample.size = min(control.ratio * min(table(Tr)), max(table(Tr))),
control.replace = TRUE, treated.sample.size = min(table(Tr)),
treated.replace = TRUE, methods = getPSAbootMethods(), parallel = TRUE,
seed = NULL, ...)Arguments
Tr
numeric (0 or 1) or logical vector of treatment indicators.
Y
vector of outcome varaible.
X
matrix or data frame of covariates used to estimate the propensity scores.
M
number of bootstrap samples to generate.
formu
formula used for estimating propensity scores. The default is to use
all covariates in X.
control.ratio
the ratio of control units to sample relative to the treatment units.
control.sample.size
the size of each bootstrap sample of control units.
control.replace
whether to use replacement when sampling from control units.
treated.sample.size
the size of each bootstrap sample of treatment units. The
default uses all treatment units for each boostrap sample.
treated.replace
whether to use replacement when sampling from treated units.
methods
a named vector of functions for each PSA method to use.
parallel
whether to run the bootstrap samples in parallel.
seed
random seed. Each iteration, i, will use a seed of seed + i.