AAA_DML: Average Adjusted Association

In ciccr: Causal Inference in Case-Control and Case-Population Studies

Average Adjusted Association

Description

Averages the log odds ratio using prospective or retrospective high-dimensional logistic regression

Usage

AAA_DML(y, t, x, type = "pro", k = 10)

Arguments

y	n-dimensional vector of binary outcomes
t	n-dimensional vector of binary treatments
x	n by d matrix of covariates
type	'pro' if the average is based on prospective regression; 'retro' if it is based on prospective regression (default = 'pro')
k	number of folds in k-fold partition (default = 10)

Value

An S3 object of type "ciccr". The object has the following elements.

est	a scalar estimate
se	standard error

References

Jun, S.J. and Lee, S. (2020). Causal Inference under Outcome-Based Sampling with Monotonicity Assumptions. https://arxiv.org/abs/2004.08318.

Examples

# use the ACS dataset included in the package
  y = ciccr::ACS$topincome
  t = ciccr::ACS$baplus
  age = ciccr::ACS$age
  x = splines::bs(age, df=6) # b-splines for age

  results = AAA_DML(y, t, x, 'pro', k=2)

ciccr documentation built on Oct. 21, 2023, 1:08 a.m.