Shifted Likelihood Factor — LF

Shifts a likelihood factor according to a shift_function and a given magnitude of the desired shift (shift_delta). In effect, get_likelihood(tmle_task) from tmle3 will instead be the likelihood from the original_lf, but for a shifted value $A'=$shift_function$(A, W)$.

Format

R6Class object.

Value

LF_base object

Constructor

define_lf(LF_shift, name, type = "density", original_lf, shift_function, ...)

name: character, the name of the factor. Should match a node name in the specification in tmle3_Task$npsem.
original_lf: LF_base object, the likelihood factor to shift.
shift_function: function, defines the shift.
shift_inverse: function, the inverse of a given shift_function.
shift_delta: numeric, specification of the magnitude of the desired shift (on the level of the treatment).
max_shifted_ratio: A numeric value indicating the maximum tolerance for the ratio of the counterfactual and observed intervention densities. In particular, the shifted value of the intervention is assigned to a given observational unit when the ratio of the counterfactual intervention density to the observed intervention density is below this value.
...: Not currently used.

Fields

original_lf: LF_base object, the likelihood factor to shift.
shift_function: function, defines the shift.
shift_inverse: function, the inverse of a given shift_function.
shift_delta: numeric, specification of the magnitude of the desired shift (on the level of the treatment).
max_shifted_ratio: A numeric value indicating the maximum tolerance for the ratio of the counterfactual and observed intervention densities. In particular, the shifted value of the intervention is assigned to a given observational unit when the ratio of the counterfactual intervention density to the observed intervention density is below this value.
...: Additional arguments passed to the base class.

References

"Stochastic Treatment Regimes.": Díaz, Iván and van der Laan, Mark (2018). In Targeted Learning in Data Science: Causal Inference for Complex Longitudinal Studies, 167–80. Springer Science & Business Media.
"Population Intervention Causal Effects Based on Stochastic Interventions.": Díaz, Iván and van der Laan, Mark J (2012). Biometrics 68 (2). Wiley Online Library: 541–49.