Compute the Pooled Mediation Shift Parameter Estimate From the Fold Specific Results

calc_pooled_med_shifts(
  med_shift_results,
  estimator = c("onestep"),
  fluc_mod_out = NULL,
  a_names,
  w_names,
  z_names,
  y_name,
  fluctuation
)

Arguments

med_shift_results: List of data frames of the mediation results across the parallelized CV procedure
estimator: The type of estimator to be fit, either "tmle" for targeted maximum likelihood estimation or "onestep" for a one-step estimator.
fluc_mod_out: An object giving values of the logistic tilting model for targeted minimum loss estimation. This type of object should be the output of the internal routines to perform this step of the TML estimation procedure, as given by fit_fluctuation.
a_names: List of exposure names
w_names: List of covariate names
z_names: List of mediator names
y_name: Outcome name
fluctuation: Type of fluctuation to be used

Value

A list containing the parameter estimate, estimated variance based on the efficient influence function (EIF), the estimate of the EIF incorporating inverse probability of censoring weights, and the estimate of the EIF without the application of such weights.

Details

Estimate the value of the pooled causal parameter alongside statistical inference for the parameter estimate based on the nuisance parameters from the fold specific results for the mediation parameter.