Context
The first version of Before You Validate is intentionally focused on declaring fixed time horizons for time-to-event validation. The broader draft also covered reference groups, prediction stratification, censoring assumptions, competing-event estimands, and reporting guidance. Those topics should be added incrementally after the fixed-horizon guide is reviewed.
Proposed follow-up sections
1. Define reference groups
Explain how the keys and shapes of probs, reals, and times encode:
- one model in one population;
- several models in one population; and
- one model across several populations.
Include compact, runnable input examples and guidance on interpretable model/cohort/site labels.
2. Choose prediction stratification
Compare:
probability_threshold for absolute-risk decisions and individual treatment trade-offs; and
ppcr for rank-based decisions under a capacity constraint.
Document that these answer different decision questions. Restore a concise treat-all/treat-none explanation where it directly supports interpretation, while moving lengthy methodological diagrams to the blog.
3. Choose a censoring heuristic
Document:
State the target quantity, the independent-censoring assumption, and the limitations under informative loss to follow-up. Link to a deeper methodological source and to an interactive blog walkthrough.
4. Choose a competing-event estimand
Compare:
excluded;
adjusted_as_censored;
adjusted_as_negative; and
adjusted_as_composite.
For every choice, state the scientific question answered—not only the mechanical recoding. Emphasize that the composite option changes the endpoint and that censoring asks a hypothetical question.
5. Add sensitivity-analysis guidance
Show how to pass multiple defensible entries in heuristics_sets. Explain that these should be pre-specified and reported as alternative estimands rather than selected after viewing the most favorable result.
6. Add a complete pre-validation checklist
Cover:
- target population and reference groups;
- decision rule and prediction strata;
- horizon units and clinical meaning;
- event-code convention;
- censoring assumptions;
- competing-event interpretation; and
- planned sensitivity analyses.
7. Connect documentation, blog, and API reference
Keep the official guide concise and action-oriented. Put detailed Aalen–Johansen derivations, internal processing steps, and advanced interactive explorers in the rtichoke Python blog. Cross-link both surfaces to prepare_performance_data_times().
Acceptance criteria
- each section answers a concrete choice users must make before validation;
- examples use only public rtichoke APIs;
- no unresolved TODOs or obsolete internal helper imports;
- terminology and argument values match the current implementation;
- all Quarto pages render successfully;
- interactive components reuse the merged
uriahtalks Quarto extension rather than duplicating JavaScript/OJS cells.
Context
The first version of Before You Validate is intentionally focused on declaring fixed time horizons for time-to-event validation. The broader draft also covered reference groups, prediction stratification, censoring assumptions, competing-event estimands, and reporting guidance. Those topics should be added incrementally after the fixed-horizon guide is reviewed.
Proposed follow-up sections
1. Define reference groups
Explain how the keys and shapes of
probs,reals, andtimesencode:Include compact, runnable input examples and guidance on interpretable model/cohort/site labels.
2. Choose prediction stratification
Compare:
probability_thresholdfor absolute-risk decisions and individual treatment trade-offs; andppcrfor rank-based decisions under a capacity constraint.Document that these answer different decision questions. Restore a concise treat-all/treat-none explanation where it directly supports interpretation, while moving lengthy methodological diagrams to the blog.
3. Choose a censoring heuristic
Document:
excluded; andadjusted.State the target quantity, the independent-censoring assumption, and the limitations under informative loss to follow-up. Link to a deeper methodological source and to an interactive blog walkthrough.
4. Choose a competing-event estimand
Compare:
excluded;adjusted_as_censored;adjusted_as_negative; andadjusted_as_composite.For every choice, state the scientific question answered—not only the mechanical recoding. Emphasize that the composite option changes the endpoint and that censoring asks a hypothetical question.
5. Add sensitivity-analysis guidance
Show how to pass multiple defensible entries in
heuristics_sets. Explain that these should be pre-specified and reported as alternative estimands rather than selected after viewing the most favorable result.6. Add a complete pre-validation checklist
Cover:
7. Connect documentation, blog, and API reference
Keep the official guide concise and action-oriented. Put detailed Aalen–Johansen derivations, internal processing steps, and advanced interactive explorers in the rtichoke Python blog. Cross-link both surfaces to
prepare_performance_data_times().Acceptance criteria
uriahtalksQuarto extension rather than duplicating JavaScript/OJS cells.