Fit propensity score regression while conditioning on mediators

fit_e_mech(data, valid_data = NULL, learners, z_names, w_names)

Arguments

data

A data.table containing the observed data, with columns in the order specified by the NPSEM (Y, Z, A, W), with column names set appropriately based on the original input data. Such a structure is merely a convenience utility to passing data around to the various core estimation routines and is automatically generated by medshift.

valid_data

A holdout data set, with columns exactly matching those appearing in the preceding argument data, to be used for estimation via cross-fitting. Optional, defaulting to NULL.

learners

A Stack (or other learner class that inherits from Lrnr_base), containing a single or set of instantiated learners from sl3, to be used in fitting a propensity score that conditions on the mediators, i.e., e = P(A | Z, W).

z_names

A character vector of the names of the columns that correspond to mediators (Z). The input for this argument is automatically generated by medshift.

w_names

A character vector of the names of the columns that correspond to baseline covariates (W). The input for this argument is automatically generated by a call to the wrapper function medshift.