prop_quant: Stratifying on the Quantiles of the Propensity Score

In FrankLef/fciR: Data and functions used with Fundamentals of Causal Inference by Babette Brumback

Stratifying on the Quantiles of the Propensity Score

Description

Stratifying on the quantiles of the propensity score.

Usage

prop_quant(
  data,
  formula,
  exposure.name,
  confound.names,
  probs = 0:4/4,
  quant_var = "pquants"
)

Arguments

data	Dataframe of raw data.
formula	Formula representing the model.
exposure.name	Name of exposure variable.
confound.names	Names of the confound variables.
probs	Vector of probability for the quantiles.
quant_var	Name of the quantile variable. Default is "pquants".

Details

Stratifying on the quantiles is useful to identify the possible interactions between the propensity scores and the exposure.

Value

Dataframe in a useable format for rsample::bootstraps.

Source

Section 10.3. p. 180.

Examples

# An example can be found in the location identified in the
# source section above at the github site
# https://github.com/FrankLef/FundamentalsCausalInference.

FrankLef/fciR documentation built on Nov. 12, 2023, 6:09 a.m.