High-Performance Open-Source Archive
multipleOutcomes() and the legacy *MO()
wrappers (coxphMO, glmMO, geeMO,
logrankMO, kmMO, quantileMO) are
removed. The package’s main entry point is now
jointCovariance(), and each component model is specified
through a constructor: glm_(), coxph_(),
logrank_(), gee_(), mmrm_(),
km_(), or quantile_(). pated()
accepts the same spec constructors via ....jointCovariance() /
pated() must now contain a column pid carrying
subject identifiers. Records with the same pid across
different data frames refer to the same subject.mmrm_() adapter for mixed models with repeated
measures.km_() adapter for Kaplan-Meier survival probabilities
(bootstrap-only, since the empirical S(t) has no closed-form
score).quantile_() adapter for between-arm quantile
differences (bootstrap-only).gee_() adapter exposing a GEE fit’s per-cluster score
and Hessian so it slots into the joint asymptotic covariance machinery
alongside other engines.conf_type = "arcsin" is fully supported in
km_() (previously silently fell back to logit
transformation).data_index defaults to 1 in every spec constructor, and
a single data frame is auto-wrapped, so
jointCovariance(spec1(...), spec2(...), data = my_df) is
the shortest valid call.data_index (must be a
positive integer scalar); jointCovariance() adds an upfront
bounds check naming the offending spec when data_index
exceeds the number of supplied data frames.pated() emits a warning when the residual variance goes
negative — typically a sign that a prognostic variable is collinear with
the primary outcome or with another prognostic.KMAdapter$fit_model() no longer strips the names off
self$estimate, so id_map entries for KM models
now carry the time_(strata)_(time) labels that
pated()’s arm lookup relies on.parseTreatmentVariableFromCall() now walks the formula
AST instead of regex-parsing the deparsed call, so formulas with nested
parentheses (e.g., y ~ arm + us(visit | pid) for
mmrm_) parse correctly.fitKMCurve() uses
survival::summary(..., extend = TRUE) consistently,
preventing NAs from leaking into the bootstrap covariance matrix when a
resample’s stratum has no observations past a requested time.pated() no longer relies on
is.null(family), which silently bound
stats::family (a function) after the family
argument was removed.jointCovariance() and
pated(). Tests are split into a fast tier (~4 s) and a
Monte Carlo tier (~25 s, opt-in via
MULTIPLEOUTCOMES_RUN_MC=1) that validates empirical
vs. theoretical covariance for single-engine, cross-engine,
partial-overlap, and kitchen-sink configurations.inst/testdata/readme_pated_reference.rds).km_().pated() extended to handle KM time-stratum parameter
vectors, including transformed-S(t) point estimates, pointwise
confidence intervals, and KM-vs-PATED curve comparison plots.
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