Skip to contents

Strategy class and subclasses

Source: R/strategy-class.R
strategy-class.Rd

The strategy class is a virtual class that defines the statistical approach for population adjustment in indirect treatment comparisons These objects are constructors that validate hyperparameters and encapsulate modelling settings before execution by outstandR()

Details

Objects of class strategy have a common structure but carry different subclasses to trigger specific S3 method dispatch

General fields

Shared by all strategies:

  • formula: The linear regression formula for the outcome model

  • family: A base R family object specifying the distribution and link

  • trt_var: The name of the treatment variable.

maic subclass

Additional fields for Matching-Adjusted Indirect Comparison:

  • n_boot: Number of bootstrap resamples for variance estimation.

stc subclass

Additional fields for Simulated Treatment Comparison:

  • N: Synthetic sample size for the target population.

gcomp_ml subclass

Additional fields for Maximum Likelihood G-computation:

  • rho: Named square matrix of covariate correlations.

  • marginal_distns: Names of the marginal distributions for covariates.

  • marginal_params: Parameters for the marginal distributions.

  • N: Synthetic sample size for the pseudo-population.

  • n_boot: Number of bootstrap resamples.

gcomp_bayes subclass

Additional fields for Bayesian G-computation:

  • rho, marginal_distns, marginal_params, N: Same as gcomp_ml.

  • ...: Additional arguments passed to the Stan engine via rstanarm::stan_glm().

mim subclass

Additional fields for Multiple Imputation Marginalization:

  • rho: Correlation matrix.

  • N: Number of iterations/simulated individuals.