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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.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.