Implementation validation studies#
Each page here reports one study of a method that cleverly implements. A page exists only for
a study registered in tests/studies/evidence/registry.py. The shared machinery in
tests/studies/evidence/ computes every verdict, and tests/unit/test_method_evidence.py checks
these pages against the committed results. Every table is generated from those results, so a stale
number is a test failure and not a reading error.
Read the pages in this order.
page |
what it gives you |
|---|---|
the eighty-five validation studies in one table, with the counts and the declared limits |
|
the three questions, the verdict rules, and the terms every study below applies |
|
every red verdict the studies publish, and the roadmap ask that owns each one |
|
the eighty-six study pages |
one row per committed test, with what it checked and the verdict its own endpoints produced |
A validation study declares property cells or names a reference. A study that names a reference is comparator-backed, and its agreement block names the comparison kind of each row. The learned-rule boundary study declares neither, so it has a page and no grid row.
To register a new study, follow adding a method row.
- Implementation validation grid
- How to read these studies
- The red-cell ledger
- Canonical point-treatment TMLE
- Weighted point-treatment TMLE
- Learned weighted point-treatment TMLE
- Ordinary multi-arm TMLE
- Stratified point-treatment TMLE
- Stratified incremental MSM
- Stratified identity-link MSM
- Stratified DR-TMLE
- Stacked point-treatment CV-TMLE
- Clustered point-treatment CV-TMLE
- Clustered point-treatment CV-TMLE at unequal cluster sizes
- Clustered TMLE intervals on a t reference at few clusters
- Clustered cross-fitted end-of-study longitudinal TMLE
- Cross-fitted clustered longitudinal TMLE on a t reference at few clusters
- Fold-evaluated point-treatment CV-TMLE
- Fold-targeted point-treatment CV-TMLE
- Repeated point-treatment cross-fitted TMLE
- Selector-based point-treatment C-TMLE
- Selector-based multi-arm C-TMLE
- C-TMLE candidate sequences
- C-TMLE0 derivative covariate
- Outcome-adaptive point-treatment C-TMLE
- Outcome-adaptive multi-arm C-TMLE
- Outcome-adaptive per-arm C-TMLE
- Outcome-adaptive per-arm C-TMLE with strata and missing data
- Outcome-adaptive per-arm C-TMLE (parametric)
- Outcome-adaptive per-arm C-TMLE (parametric crossfit)
- Outcome-adaptive per-arm C-TMLE (parametric extensions)
- Canonical DR-TMLE
- What was compared
- What the solver diagnostics do and do not compare
- The two implementations reach different roots when the outcome regression is wrong
- Accuracy against known truth
- Agreement with the canonical implementation
- Repeated-sampling properties
- Measured values and declared margins
- What a red double-robustness cell means here
- Limitations
- Reproduction
- Multi-arm DR-TMLE
- Ordinary missing-outcome TMLE
- Ordinary missing-outcome natural-course TMLE
- Stacked missing-outcome natural-course CV-TMLE
- Stacked arm-indexed missing-outcome CV-TMLE
- Missing-outcome attributable-effect TMLE
- Ordinary controlled direct-effect TMLE
- Randomized missing-outcome DR-TMLE
- Observational missing-data DR-TMLE
- Randomized multi-arm missing-outcome DR-TMLE
- Point-treatment MSM projection
- Deterministic point-treatment regimes
- CV-TMLE of the fold-local learned-rule value
- CV-TMLE of the fold-local learned-rule value at exceptional and weak-blip laws
- Stochastic point-treatment regimes
- Continuous modified treatment policies
- Point modified treatment policies
- Incremental propensity interventions
- Ordinary end-of-study longitudinal TMLE
- Ordinary weighted end-of-study longitudinal TMLE
- Ordinary categorical longitudinal TMLE
- Stochastic categorical longitudinal TMLE
- Longitudinal modified treatment policies
- Longitudinal incremental interventions
- Longitudinal incremental propensity-score interventions under dropout
- Categorical incremental policies
- Vector modified treatment policies
- MTP boundaries
- MTP pricing
- MTP tuning
- Sequentially doubly robust estimation
- Ordinary longitudinal MSM projection
- Cross-fitted longitudinal MSM projection
- Cross-fitted end-of-study longitudinal TMLE
- Cross-fitted weighted end-of-study longitudinal TMLE
- Cross-fitted categorical longitudinal TMLE
- Ordinary survival-curve longitudinal TMLE
- Cross-fitted survival-curve longitudinal TMLE
- Ordinary competing-risk longitudinal TMLE
- Cross-fitted competing-risk longitudinal TMLE
- Point-treatment survival
- Cross-fitted point-treatment survival
- Point survival hazard
- Point survival curve
- Point survival curve crossfit
- Point-treatment survival policies
- TMLE on a declared known treatment mechanism
- DR-TMLE on a declared known treatment mechanism
- DR-TMLE with one inconsistent nuisance
- LTMLE on declared known node mechanisms
- Sequential g-computation and IPW
- Structural nested mean model
- Parametric g-formula
- Repeated-outcome longitudinal TMLE
- Repeated-outcome longitudinal IPSI
- Omitted-variable bound standard error
- Calibration-slope warning
- Default simultaneous bands
- Full-refit bootstrap and derived contrasts