COCA survival estimator: NOT supported (returns NA)

COCA (Correlated Outcome Control Approach) regresses the negative control W on the outcome Y (W ~ y + X) and recovers the causal effect as a ratio \(-\hat\beta_X / \hat\beta_Y\). This places the outcome on the right-hand side of the regression, which is structurally impossible when the outcome is a survival::Surv object (time-to-event). COCA is therefore unsupported for survival outcomes and always returns list(beta=NA, se=NA, pvalue=NA).

Usage

fit_coca_surv(time, event, X, w, covars = NULL, ...)

Arguments

time: Numeric follow-up time vector (length n).
event: Numeric 0/1 event indicator (length n).
X: Numeric exposure vector (length n).
w: Numeric NC vector (length n).
covars: Optional data frame of covariates (n rows).
...: Ignored (accepted for signature compatibility).

Value

list(beta = NA, se = NA, pvalue = NA) with an informative "reason" attribute.

Examples

set.seed(1)
dat <- generate_toy_data(n = 200, outcome_type = "survival", seed = 1)
fit_coca_surv(dat$surv_time, dat$surv_event, dat$X, dat$W[, 1])
#> $beta
#> [1] NA
#> 
#> $se
#> [1] NA
#> 
#> $pvalue
#> [1] NA
#> 
#> attr(,"reason")
#> [1] "COCA regresses W on Y (W ~ y + X), placing the outcome on the RHS, which is impossible with a Surv object. COCA is unsupported for survival outcomes."
# $beta [1] NA (COCA unsupported for survival outcomes)