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()
Objects of class strategy have a common structure but carry
different subclasses to trigger specific S3 method dispatch
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.
Additional fields for Matching-Adjusted Indirect Comparison:
n_boot: Number of bootstrap resamples for variance estimation.
Additional fields for Simulated Treatment Comparison:
N: Synthetic sample size for the target population.
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.
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().
Additional fields for Multiple Imputation Marginalization:
rho: Correlation matrix.
N: Number of iterations/simulated individuals.