Estimate the causal effect by G-computation with jackknife variance estimation.

Estimate the causal effect by G-computation with jackknife variance estimation.

Usage

gcomp_jack(
  .data,
  .outcome,
  .treatment,
  .formula_rhs,
  .estimand = c("cfmean", "ATE"),
  .weights,
  .repweights,
  .type = c("JK1", "JK2"),
  .by = NULL
)

Arguments

.data

A tibble that contains the data.

.outcome

The name of the outcome variable.

.treatment

The name of the treatment binary variable, only allowed to be 0 or 1.

.formula_rhs

The right-hand side of the regression formula.

.estimand

Specify the estimand. 'cfmean' or 'ATE'.

.weights

The name of the sampling weights.

.repweights

The name of the replicate weights.

.type

The variation of jackknife variance estimation. 'JK1' or 'JK2'.

.by

The variable to be used for heterogeneity analysis. If NULL, the entire population is used.