boot.ctree: Stratification using classification trees for bootstrapping.

In PSAboot: Bootstrapping for Propensity Score Analysis

Stratification using classification trees for bootstrapping.

Description

Stratification using classification trees for bootstrapping.

Usage

boot.ctree(Tr, Y, X, X.trans, formu, minStrata = 5, ...)

Arguments

Tr	vector indicating treatment assignment.
Y	vector of outcome.
X	matrix or data frame of covariates.
X.trans	a data frame of X with factors recoded. See cv.trans.psa
formu	the formula to use to estimate propensity scores. Note that the dependent varaible (i.e. treatment varaible) name will be updated using the Tr vector.
minStrata	minimum number of treatment or control units within a strata to include that strata.
...	other parameters passed from PSAboot

Value

a list with three elements:

summary

a named numeric vector (with at minimum estimate, ci.min, and ci.max but other values allowed)

balance

a named numeric vector with one element per covariate listed in X.trans representing a balance statistic (usually standardized effect size after adjustment)

details

an arbitrary object that contains the full results of the analysis

PSAboot documentation built on Oct. 24, 2023, 1:06 a.m.