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Compute and Attach CDE Values to a DGM Object

Source: R/oc_analyses_gbsg.R
compute_dgm_cde.Rd

Calculates Controlled Direct Effect (CDE) hazard ratios from the super-population potential outcomes (theta_0, theta_1) and attaches them to the DGM's hazard_ratios list. This enables automatic CDE detection by build_estimation_table.

Usage

compute_dgm_cde(dgm, harm_col = NULL)

Arguments

dgm

A DGM object (e.g., from create_gbsg_dgm or generate_aft_dgm_flex). Must contain df_super_rand with columns theta_0 and theta_1.

harm_col

Character. Name of the subgroup indicator column in dgm$df_super_rand. If NULL (default), auto-detected from flag.harm, flag_harm, or H.

Value

The DGM object with CDE values added to dgm$hazard_ratios (CDE, CDE_harm, CDE_no_harm) and to top-level fields (dgm$CDE, dgm$cde_H, dgm$cde_Hc).

Details

The CDE for subgroup S is defined as:

CDE(S) = mean(exp(theta_1[S])) / mean(exp(theta_0[S]))

which is the ratio of average hazard contributions on the natural scale. This differs from the AHR (exp(mean(loghr_po))) due to Jensen's inequality. In the notation of Leon et al. (2024), CDE corresponds to theta-ddagger.

The function detects the subgroup indicator column automatically, checking for flag.harm, flag_harm, and H in the super-population data frame.

See also

build_estimation_table, get_dgm_hr

Examples

if (FALSE) { # \dontrun{
dgm <- create_gbsg_dgm(model = "alt", k_inter = 2.0)
dgm <- compute_dgm_cde(dgm)
dgm$hazard_ratios$CDE_harm   # theta-ddagger(H)
dgm$hazard_ratios$CDE         # theta-ddagger overall
} # }