First CRAN submission.
seed argument never changes the global stream.stress_report(), stress_tables() and
stress_html() have no default output location; nothing is
written unless a directory or file is given.stress_verdict() and tipping_point() gain
examples.Authors@R; the
citation reads the version from the package metadata.standard_plan() now shifts the tipping family at the
contrast visit unless shift_visits is given; before, an
omitted shift_visits shifted every imputed visit, which
changed the tipping estimand silently.stress_design(): design-stage use. Simulates a planned
trial over a grid of sample sizes and effect sizes and reports the
robustness power (significant and robust) next to the conventional
power, the verdict rates among significant results, the one-subject
fragility, and optionally the deletion search and the delta-adjustment
margin; plot() draws power and robustness power against the
sample size, and print() names the smallest sample size
that reaches a target robustness power.stress_ranktest(): Wilcoxon rank-sum and van Elteren
tests at the contrast visit (model-free family).
simulate_trial() gains heavy-tailed errors,
heteroscedastic visits, MNAR dropout and effect modification;
stress_calibrate() passes them through.
Observed-margins weighting fixed for three or more arms.
Reference-based imputation seeds each draw on the worker, so results no longer depend on the number of cores.
The fitter reads the model matrix and covariance parameters through mmrm’s public accessors.
Verdicts, reports and tables state how many refits did not converge.
mask_ids() replaces subject identifiers with
sequence numbers; on by default in stress_html().
run_plan() starts one worker cluster and shares it
across families.
stress_sap() and the installed template give the
statistical-analysis-plan text for a pre-specified stress test.
Validation vignette; CITATION; Nathan Hogan credited for the SAS reference validation.
mmrm fit
(stress_spec_mmrm()) and from an ADaM BDS data set
(stress_spec_adam()).active chooses the comparison;
stress_visits() gives the contrast at every visit;
run_plans() runs several endpoints or comparisons and
summarises them together.standard_plan(): the recommended, citable set of
families.stress_estimand(): intercurrent-event strategies
(treatment policy, hypothetical, while on treatment, composite) derived
from an event table.stress_explain(): attributes an alternative’s shift to
subjects.stress_tables() (CSV, Word, RTF),
stress_log() (audit trail with the plan’s hash),
stress_html() (interactive report).simulate_trial() and stress_calibrate():
pre-trial calibration of the verdict.stress_plan(),
run_plan(), stress_report().stress_weights() and the weights setting
(equal versus observed-margins least-squares means); cLDA estimator;
fast path for the re-randomisation test.stress_reference()), the sensitivity/supplementary
role, the greedy deletion search
(stress_fragility()), the estimator-class family
(stress_estimator()).