Validation, NCE analysis, per-replicate oracle for landmark/naive, RCT truths script, resumable experiment runner

- W0 harm validation (40 reps): CCW and sequential ITT unbiased for their truths (|z| <= 0.7)
- PVI models fitted separately inside and after the window
- experiments.yml grid (8 worlds x 3 scenarios; designs x V1-V4; NCE; RCTs); smoke run clean

Co-Authored-By: Claude Opus 5.5 <[email protected]>

pvisim/R/limits.R

@@ -0,0 +1,29 @@
+# Own estimands of the non-interventional designs (plan 5.5). The landmark and naive
+# contrasts have no intervention that defines them; their own estimand is what the same
+# estimator gives with every confounder measured (oracle): exact severity, true frailty
+# and smoking, and the latent physician traits. A large-n limit is too noisy (the
+# landmark estimator has few treated patients), so the oracle estimator is run on every
+# replicate's own data: estimation bias = mean(estimate - oracle estimate), paired, and
+# the oracle mean estimates the own estimand.
+
+#' The replicate's records with the hidden truth in place of the claims proxies.
+oracle_records <- function(rec) {
+  o <- rec
+  o$pm <- merge(rec$pm[, .(id, t)], rec$hidden_pm, by = c("id", "t"))[, .(id, t, sev_obs = z)]
+  h <- rec$hidden
+  o$patients <- merge(copy(rec$patients)[, c("frailty_index", "smoking") := NULL],
+                      h[, .(id, frailty_index = frailty, smoking = smoking_true, skill, style)], by = "id")
+  o$extra_covs <- c("skill", "style")
+  o
+}
+
+#' Oracle versions of the landmark and naive designs (V1, patient-level SE).
+run_oracle <- function(rec, outcomes = c(male = "t_male", disease = "t_disease", nco1 = "t_nco1", nco2 = "t_nco2")) {
+  o <- oracle_records(rec)
+  rbindlist(lapply(names(outcomes), function(nm) {
+    lm <- est_landmark(o, outcomes[[nm]], "V1_ignore", extra_covs = o$extra_covs)
+    nv <- est_naive(o, outcomes[[nm]], "V1_ignore", extra_covs = o$extra_covs)
+    rbind(cbind(design = "landmark", lm), cbind(design = "naive", nv))[
+      , `:=`(outcome = nm, contrast = "early_none", variant = "oracle", se = se_patient)]
+  }))
+}