drcount: Doubly robust estimator of the average treatment effect for...
In precmed: Precision Medicine

drcount

R Documentation

Doubly robust estimator of the average treatment effect for count data

Description

Doubly robust estimator of the average treatment effect between two treatments, which is the rate ratio of treatment 1 over treatment 0 for count outcomes.

Usage

drcount(
  y,
  trt,
  x.cate,
  x.ps,
  time,
  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 count 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.
`time`	A numeric vector of size `n` with each element representing the log-transformed person-years of follow-up for each subject.
`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 allow for treatment-covariate interaction by `x`. If `TRUE`, interactions will be assumed only if at least 10 patients received each treatment option. Default is `TRUE`.