drmean: Doubly robust estimator of the average treatment effect for...

In precmed: Precision Medicine

Doubly robust estimator of the average treatment effect for continuous data

Description

Doubly robust estimator of the average treatment effect between two treatments, which is the mean difference of treatment 1 over treatment 0 for continuous outcomes.

Usage

drmean(
  y,
  trt,
  x.cate,
  x.ps,
  ps.method = "glm",
  minPS = 0.01,
  maxPS = 0.99,
  interactions = TRUE
)

Arguments

y	A numeric vector of size n with each element representing the observed continuous outcome for each subject.
trt	A numeric vector (in {0, 1}) of size n with each element representing the treatment received for each subject.
x.cate	A numeric matrix of dimension n by p.cate with each column representing each baseline covariate specified in the outcome model for all subjects.
x.ps	A numeric matrix of dimension n by p.ps + 1 with a leading column of 1 as the intercept and each remaining column representing each baseline covariate specified in the propensity score model for all subjects
ps.method	A character value for the method to estimate the propensity score. Allowed values include one of: 'glm' for logistic regression with main effects only (default), or 'lasso' for a logistic regression with main effects and LASSO penalization on two-way interactions (added to the model if interactions are not specified in ps.model). Relevant only when ps.model has more than one variable.
minPS	A numerical value between 0 and 1 below which estimated propensity scores should be truncated. Default is 0.01.
maxPS	A numerical value between 0 and 1 above which estimated propensity scores should be truncated. Must be strictly greater than minPS. Default is 0.99.
interactions	A logical value indicating whether the outcome model should assume interactions between x and trt. If TRUE, interactions will be assumed only if at least 10 patients received each treatment option. Default is TRUE.

Value

Return a list of 4 elements:

• mean.diff: A numeric value of the estimated mean difference.

• mean.diff0: A numeric value of the estimated mean difference in treatment group 0.

• mean.diff1: A numeric value of the estimated mean difference in treatment group 1.

precmed documentation built on Oct. 6, 2024, 1:07 a.m.