The log-rank is one member of a family that differs only in how much each
event time counts. Nothing else changes: the counts it reports stay counts
whatever the weight, and the published-dataset results are unmoved.
Steps to first violation with clean runs right-censored at the budget, since
per-run yield is a binary at 11 to 45 percent and separating two arms on it
would need roughly 80 runs per arm. Kaplan-Meier, log-rank, Wilcoxon rank-sum
with Vargha-Delaney A12, Holm within each family.
A hand-rolled log-rank that is subtly wrong is a silent-wrong-number generator
and would be believed, so every statistic is validated against a published
worked example with the source named in the test: R survdiff on aml, Freireich
6-MP, Hollander and Wolfe 1973 for the rank sum, printed p.adjust output for
Holm. Two could not be: the k>2 log-rank, guarded by calibration instead, and
the tie-corrected variance, checked against an exact permutation variance.
Failed and timed-out runs are excluded as missing data and counted by reason,
never treated as censored observations, which would bias the result.
Claude-Session: https://claude.ai/code/session_01A5KmftdEJ49A9z5mF5ESrX
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