compute_influence_terms: Compute Influence Terms

In SensIAT: Sensitivity Analysis for Irregular Assessment Times

Compute Influence Terms

Description

This function computes the influence terms for the marginal outcome model sensitivity analysis. It is a generic function that can handle different types of outcome models.

Usage

compute_influence_terms(outcome.model, intensity.model, alpha, data, ...)

## Default S3 method:
compute_influence_terms(
  outcome.model,
  intensity.model,
  alpha,
  data,
  id,
  base,
  ...
)

## S3 method for class ''SensIAT::Single-index-outcome-model''
compute_influence_terms(
  outcome.model,
  intensity.model,
  alpha,
  data,
  base,
  tolerance = .Machine$double.eps^(1/3),
  na.action = na.fail,
  id = NULL,
  time = NULL,
  ...
)

Arguments

outcome.model	The outcome model fitted to the data.
intensity.model	The intensity model fitted to the data.
alpha	A numeric vector representing the sensitivity parameter.
data	A data frame containing the observations.
...	Additional arguments passed to the method.
id	A variable representing the patient identifier.
base	A spline basis object.
tolerance	Numeric value indicating the tolerance for integration, default is .Machine$double.eps^(1/3).
na.action	Function to handle missing values, default is na.fail.
time	Variable indicating the time variable in the data, by Default will be extracted from the intensity model response.

Methods (by class)

• compute_influence_terms(default): Generic method, which throws a not implemented error.

• compute_influence_terms(`SensIAT::Single-index-outcome-model`): Optimized method for the single index model.

SensIAT documentation built on Sept. 9, 2025, 5:50 p.m.