Stratified incremental MSM#

This study validates three stratified targets of ordinary point-treatment TMLE with baseline strata, strata=["V"]: incremental propensity-score interventions, marginal structural models (MSMs) with a logit link or a continuous dose, and the cross-fitted natural-course mean with a missing outcome. A stratum parameter is the marginal parameter of the law inside one of a fixed number of baseline strata. The construction is the marginal result applied inside each cell of a finite partition, which the natural-extension verdicts record as part (i).

Each target solves one score block \(I(V=s) H_s / P_n(V=s)\) for each equation of its targeting. Each stratum curve is \(I(V=s) D_s / P_n(V=s)\). The incremental fit alternates outcome blocks and treatment-mechanism blocks. The linked MSM fit takes its stratum coefficients from a nested fluctuation of the blocks at each stratum’s own coefficients. Point-treatment TMLE states each construction.

What was tested#

setting

declaration

law L1

the baseline-strata law: \(V \in \{0, 1, 2\}\) with probabilities 0.5, 0.3 and 0.2, \(W \in \{0, 1, 2\}\) given \(V\), a binary treatment and a binary outcome. tests/studies/stratified_alternating_law.py computes every truth and every efficient influence function exactly over the 36 support points

law L2

L1’s \(V\) and \(W\), a dose \(A \sim N(0.5 W - 0.4 V, 1)\), a continuous outcome for the identity link and a binary outcome for the logit link, both with an \(A V\) term

L1 with a missing outcome

L1, with the outcome observed with probability \(\operatorname{expit}(1.1 - 0.3 A + 0.2 W - 0.25 V)\)

primary scenario

stratified_incremental: the incremental means at odds multipliers 1, 2 and 0.5 and their two contrasts, marginal and in each stratum, \(n = 2000\), 1,600 replications

fits

in sample, with main-terms logistic regressions on \((A, W, V)\) and \((W, V)\), which are correct for L1. The natural-course fits are cross-fitted on ten folds

Monte Carlo inference

exact 99% intervals around every rate, and 99% intervals around every primary endpoint

The comparator is R npcausal ipsi at commit 56a5ac1. npcausal has no stratified estimator, so the runner calls ipsi once per stratum subset and multiplier, and once per multiplier on every row for the marginal means. The two implementations differ in two declared ways.

difference

effect

npcausal cross-fits its nuisances over two splits. Its single-split path selects no training rows at 56a5ac1

the paired difference scales like \(1/n_s\), so it is largest in the smallest stratum

npcausal fits SL.glm.interaction. Inside a stratum it is saturated. On every row it has no \(A{:}W{:}V\) term, so it is correct for L1 but not saturated

the marginal rows compare two correct but different regressions

The MSM and natural-course targets have no stratified comparator. The property cells measure them against the exact truths.

Accuracy against known truth#

law

estimand

what was tested

implementation

bias (99% interval)

coverage

SE ratio

result

binary law with three unequal baseline strata, three incremental odds multipliers

ate_ipsi[odds x0.5 vs natural course]

difference in means under the incremental interventions “multiply the treatment odds by 0.5” against “leave the observed treatment mechanism unchanged”

cleverly incremental TMLE with baseline strata

-0.000095 to 0.000314

0.9469

0.9790

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ate_ipsi[odds x0.5 vs natural course]

difference in means under the incremental interventions “multiply the treatment odds by 0.5” against “leave the observed treatment mechanism unchanged”

R npcausal ipsi, once per stratum subset and on every row

-0.000405 to 0.000021

0.9400

0.9529

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ate_ipsi[odds x0.5 vs natural course][V=0]

difference in means under the incremental interventions “multiply the treatment odds by 0.5” against “leave the observed treatment mechanism unchanged”, in stratum V=0

cleverly incremental TMLE with baseline strata

-0.000276 to 0.000378

0.9494

0.9891

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ate_ipsi[odds x0.5 vs natural course][V=0]

difference in means under the incremental interventions “multiply the treatment odds by 0.5” against “leave the observed treatment mechanism unchanged”, in stratum V=0

R npcausal ipsi, once per stratum subset and on every row

-0.000614 to 0.000058

0.9437

0.9734

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ate_ipsi[odds x0.5 vs natural course][V=1]

difference in means under the incremental interventions “multiply the treatment odds by 0.5” against “leave the observed treatment mechanism unchanged”, in stratum V=1

cleverly incremental TMLE with baseline strata

-0.000137 to 0.000573

0.9475

0.9686

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ate_ipsi[odds x0.5 vs natural course][V=1]

difference in means under the incremental interventions “multiply the treatment odds by 0.5” against “leave the observed treatment mechanism unchanged”, in stratum V=1

R npcausal ipsi, once per stratum subset and on every row

-0.000475 to 0.000266

0.9381

0.9439

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ate_ipsi[odds x0.5 vs natural course][V=2]

difference in means under the incremental interventions “multiply the treatment odds by 0.5” against “leave the observed treatment mechanism unchanged”, in stratum V=2

cleverly incremental TMLE with baseline strata

-0.000182 to 0.000380

0.9469

0.9787

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ate_ipsi[odds x0.5 vs natural course][V=2]

difference in means under the incremental interventions “multiply the treatment odds by 0.5” against “leave the observed treatment mechanism unchanged”, in stratum V=2

R npcausal ipsi, once per stratum subset and on every row

-0.000385 to 0.000214

0.9375

0.9453

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ate_ipsi[odds x2 vs natural course]

difference in means under the incremental interventions “multiply the treatment odds by two” against “leave the observed treatment mechanism unchanged”

cleverly incremental TMLE with baseline strata

-0.000348 to 0.000071

0.9481

0.9813

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ate_ipsi[odds x2 vs natural course]

difference in means under the incremental interventions “multiply the treatment odds by two” against “leave the observed treatment mechanism unchanged”

R npcausal ipsi, once per stratum subset and on every row

-0.000004 to 0.000433

0.9419

0.9551

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ate_ipsi[odds x2 vs natural course][V=0]

difference in means under the incremental interventions “multiply the treatment odds by two” against “leave the observed treatment mechanism unchanged”, in stratum V=0

cleverly incremental TMLE with baseline strata

-0.000374 to 0.000273

0.9487

0.9911

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ate_ipsi[odds x2 vs natural course][V=0]

difference in means under the incremental interventions “multiply the treatment odds by two” against “leave the observed treatment mechanism unchanged”, in stratum V=0

R npcausal ipsi, once per stratum subset and on every row

-0.000111 to 0.000551

0.9456

0.9788

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ate_ipsi[odds x2 vs natural course][V=1]

difference in means under the incremental interventions “multiply the treatment odds by two” against “leave the observed treatment mechanism unchanged”, in stratum V=1

cleverly incremental TMLE with baseline strata

-0.000638 to 0.000125

0.9481

0.9676

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ate_ipsi[odds x2 vs natural course][V=1]

difference in means under the incremental interventions “multiply the treatment odds by two” against “leave the observed treatment mechanism unchanged”, in stratum V=1

R npcausal ipsi, once per stratum subset and on every row

-0.000217 to 0.000576

0.9356

0.9472

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ate_ipsi[odds x2 vs natural course][V=2]

difference in means under the incremental interventions “multiply the treatment odds by two” against “leave the observed treatment mechanism unchanged”, in stratum V=2

cleverly incremental TMLE with baseline strata

-0.000519 to 0.000140

0.9425

0.9720

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ate_ipsi[odds x2 vs natural course][V=2]

difference in means under the incremental interventions “multiply the treatment odds by two” against “leave the observed treatment mechanism unchanged”, in stratum V=2

R npcausal ipsi, once per stratum subset and on every row

-0.000113 to 0.000591

0.9350

0.9377

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[natural course]

mean under the incremental intervention leave the observed treatment mechanism unchanged

cleverly incremental TMLE with baseline strata

-0.000288 to 0.0011

0.9487

0.9870

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[natural course]

mean under the incremental intervention leave the observed treatment mechanism unchanged

R npcausal ipsi, once per stratum subset and on every row

-0.000288 to 0.0011

0.9487

0.9870

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[natural course][V=0]

mean under the incremental intervention leave the observed treatment mechanism unchanged, in stratum V=0

cleverly incremental TMLE with baseline strata

-0.000797 to 0.0013

0.9450

0.9841

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[natural course][V=0]

mean under the incremental intervention leave the observed treatment mechanism unchanged, in stratum V=0

R npcausal ipsi, once per stratum subset and on every row

-0.000797 to 0.0013

0.9456

0.9844

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[natural course][V=1]

mean under the incremental intervention leave the observed treatment mechanism unchanged, in stratum V=1

cleverly incremental TMLE with baseline strata

-0.000558 to 0.0018

0.9406

0.9712

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[natural course][V=1]

mean under the incremental intervention leave the observed treatment mechanism unchanged, in stratum V=1

R npcausal ipsi, once per stratum subset and on every row

-0.000558 to 0.0018

0.9406

0.9717

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[natural course][V=2]

mean under the incremental intervention leave the observed treatment mechanism unchanged, in stratum V=2

cleverly incremental TMLE with baseline strata

-0.000641 to 0.0014

0.9544

1.0341

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[natural course][V=2]

mean under the incremental intervention leave the observed treatment mechanism unchanged, in stratum V=2

R npcausal ipsi, once per stratum subset and on every row

-0.000641 to 0.0014

0.9544

1.0352

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[odds x0.5]

mean under the incremental intervention multiply the treatment odds by 0.5

cleverly incremental TMLE with baseline strata

-0.000223 to 0.0012

0.9500

0.9923

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[odds x0.5]

mean under the incremental intervention multiply the treatment odds by 0.5

R npcausal ipsi, once per stratum subset and on every row

-0.000529 to 0.000953

0.9500

0.9887

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[odds x0.5][V=0]

mean under the incremental intervention multiply the treatment odds by 0.5, in stratum V=0

cleverly incremental TMLE with baseline strata

-0.000793 to 0.0014

0.9444

0.9889

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[odds x0.5][V=0]

mean under the incremental intervention multiply the treatment odds by 0.5, in stratum V=0

R npcausal ipsi, once per stratum subset and on every row

-0.0011 to 0.0010

0.9437

0.9880

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[odds x0.5][V=1]

mean under the incremental intervention multiply the treatment odds by 0.5, in stratum V=1

cleverly incremental TMLE with baseline strata

-0.000448 to 0.0022

0.9413

0.9777

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[odds x0.5][V=1]

mean under the incremental intervention multiply the treatment odds by 0.5, in stratum V=1

R npcausal ipsi, once per stratum subset and on every row

-0.000775 to 0.0018

0.9413

0.9772

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[odds x0.5][V=2]

mean under the incremental intervention multiply the treatment odds by 0.5, in stratum V=2

cleverly incremental TMLE with baseline strata

-0.000664 to 0.0016

0.9513

1.0259

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[odds x0.5][V=2]

mean under the incremental intervention multiply the treatment odds by 0.5, in stratum V=2

R npcausal ipsi, once per stratum subset and on every row

-0.000852 to 0.0014

0.9494

1.0270

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[odds x2]

mean under the incremental intervention multiply the treatment odds by two

cleverly incremental TMLE with baseline strata

-0.000435 to 0.000964

0.9469

0.9808

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[odds x2]

mean under the incremental intervention multiply the treatment odds by two

R npcausal ipsi, once per stratum subset and on every row

-0.000082 to 0.0013

0.9450

0.9822

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[odds x2][V=0]

mean under the incremental intervention multiply the treatment odds by two, in stratum V=0

cleverly incremental TMLE with baseline strata

-0.000890 to 0.0013

0.9506

0.9804

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[odds x2][V=0]

mean under the incremental intervention multiply the treatment odds by two, in stratum V=0

R npcausal ipsi, once per stratum subset and on every row

-0.000621 to 0.0015

0.9487

0.9803

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[odds x2][V=1]

mean under the incremental intervention multiply the treatment odds by two, in stratum V=1

cleverly incremental TMLE with baseline strata

-0.000801 to 0.0016

0.9456

0.9615

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[odds x2][V=1]

mean under the incremental intervention multiply the treatment odds by two, in stratum V=1

R npcausal ipsi, once per stratum subset and on every row

-0.000368 to 0.0020

0.9463

0.9622

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[odds x2][V=2]

mean under the incremental intervention multiply the treatment odds by two, in stratum V=2

cleverly incremental TMLE with baseline strata

-0.000773 to 0.0011

0.9513

1.0324

pass

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[odds x2][V=2]

mean under the incremental intervention multiply the treatment odds by two, in stratum V=2

R npcausal ipsi, once per stratum subset and on every row

-0.000350 to 0.0016

0.9463

1.0316

pass

Agreement with the canonical implementation#

Comparator-backed: a paired comparison with npcausal-stratified on the same samples. Each row reports estimate equivalence within the declared margin, the RMSE ratio and the coverage difference, and names its comparison kind.

law

estimand

what was compared

paired difference

share of margin used

RMSE ratio bound

coverage difference

comparison kind

calibration resolution

result

binary law with three unequal baseline strata, three incremental odds multipliers

ate_ipsi[odds x0.5 vs natural course]

difference in means under the incremental interventions “multiply the treatment odds by 0.5” against “leave the observed treatment mechanism unchanged”

0.000302

0.6214

0.9714

0.0069

different estimator

0.0394 vs 0.0500

equivalent

binary law with three unequal baseline strata, three incremental odds multipliers

ate_ipsi[odds x0.5 vs natural course][V=0]

difference in means under the incremental interventions “multiply the treatment odds by 0.5” against “leave the observed treatment mechanism unchanged”, in stratum V=0

0.000329

0.4264

0.9835

0.0056

related target

0.0358 vs 0.0500

equivalent

binary law with three unequal baseline strata, three incremental odds multipliers

ate_ipsi[odds x0.5 vs natural course][V=1]

difference in means under the incremental interventions “multiply the treatment odds by 0.5” against “leave the observed treatment mechanism unchanged”, in stratum V=1

0.000322

0.3818

0.9715

0.0094

related target

0.0180 vs 0.0500

superior

binary law with three unequal baseline strata, three incremental odds multipliers

ate_ipsi[odds x0.5 vs natural course][V=2]

difference in means under the incremental interventions “multiply the treatment odds by 0.5” against “leave the observed treatment mechanism unchanged”, in stratum V=2

0.000184

0.2724

0.9574

0.0094

related target

0.0376 vs 0.0500

equivalent

binary law with three unequal baseline strata, three incremental odds multipliers

ate_ipsi[odds x2 vs natural course]

difference in means under the incremental interventions “multiply the treatment odds by two” against “leave the observed treatment mechanism unchanged”

-0.000353

0.7097

0.9722

0.0062

different estimator

0.0444 vs 0.0500

equivalent

binary law with three unequal baseline strata, three incremental odds multipliers

ate_ipsi[odds x2 vs natural course][V=0]

difference in means under the incremental interventions “multiply the treatment odds by two” against “leave the observed treatment mechanism unchanged”, in stratum V=0

-0.000271

0.3558

0.9881

0.0031

related target

0.0309 vs 0.0500

equivalent

binary law with three unequal baseline strata, three incremental odds multipliers

ate_ipsi[odds x2 vs natural course][V=1]

difference in means under the incremental interventions “multiply the treatment odds by two” against “leave the observed treatment mechanism unchanged”, in stratum V=1

-0.000436

0.4810

0.9759

0.0125

related target

0.0171 vs 0.0500

superior

binary law with three unequal baseline strata, three incremental odds multipliers

ate_ipsi[odds x2 vs natural course][V=2]

difference in means under the incremental interventions “multiply the treatment odds by two” against “leave the observed treatment mechanism unchanged”, in stratum V=2

-0.000428

0.5397

0.9523

0.0075

related target

0.0243 vs 0.0500

equivalent

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[natural course]

mean under the incremental intervention leave the observed treatment mechanism unchanged

-5.990e-15

3.723e-12

1.0000

0

different estimator

1.196e-13 vs 0.0500

equivalent

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[natural course][V=0]

mean under the incremental intervention leave the observed treatment mechanism unchanged, in stratum V=0

-3.209e-17

1.334e-14

1.0000

-0.000625

related target

0.000004 vs 0.0500

equivalent

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[natural course][V=1]

mean under the incremental intervention leave the observed treatment mechanism unchanged, in stratum V=1

-2.741e-17

9.874e-15

1.0000

0

related target

0.000016 vs 0.0500

equivalent

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[natural course][V=2]

mean under the incremental intervention leave the observed treatment mechanism unchanged, in stratum V=2

-3.006e-14

1.272e-11

1.0000

0

related target

0.0020 vs 0.0500

equivalent

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[odds x0.5]

mean under the incremental intervention multiply the treatment odds by 0.5

0.000302

0.1756

0.9986

0

different estimator

0.0100 vs 0.0500

equivalent

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[odds x0.5][V=0]

mean under the incremental intervention multiply the treatment odds by 0.5, in stratum V=0

0.000329

0.1305

1.0009

0.000625

related target

0.0046 vs 0.0500

equivalent

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[odds x0.5][V=1]

mean under the incremental intervention multiply the treatment odds by 0.5, in stratum V=1

0.000322

0.1062

1.0005

0

related target

0.0038 vs 0.0500

equivalent

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[odds x0.5][V=2]

mean under the incremental intervention multiply the treatment odds by 0.5, in stratum V=2

0.000184

0.0694

1.0010

0.0019

related target

0.0054 vs 0.0500

equivalent

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[odds x2]

mean under the incremental intervention multiply the treatment odds by two

-0.000353

0.2171

1.0020

0.0019

different estimator

0.0033 vs 0.0500

equivalent

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[odds x2][V=0]

mean under the incremental intervention multiply the treatment odds by two, in stratum V=0

-0.000271

0.1081

1.0009

0.0019

related target

0.0029 vs 0.0500

equivalent

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[odds x2][V=1]

mean under the incremental intervention multiply the treatment odds by two, in stratum V=1

-0.000436

0.1586

1.0008

-0.000625

related target

0.0038 vs 0.0500

equivalent

binary law with three unequal baseline strata, three incremental odds multipliers

ey_ipsi[odds x2][V=2]

mean under the incremental intervention multiply the treatment odds by two, in stratum V=2

-0.000428

0.1916

0.9994

0.0050

related target

0.0060 vs 0.0500

equivalent

Repeated-sampling properties#

property

cell

role

what was tested

what must hold

measured

result

double_robustness

continuous_identity_marginal_a__outcome_correct

positive

dose coefficient of the identity-link dose MSM (1, a) over the grid, marginal: only the outcome regression is correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias -0.0027 to 0.0069, margin 0.0209, SE ratio 0.9949

pass

double_robustness

continuous_identity_marginal_intercept__outcome_correct

positive

intercept coefficient of the identity-link dose MSM (1, a) over the grid, marginal: only the outcome regression is correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias -0.0032 to 0.0019, margin 0.0111, SE ratio 1.1519

pass

double_robustness

continuous_identity_v0_a__outcome_correct

positive

dose coefficient of the identity-link dose MSM (1, a) over the grid, in stratum V = 0: only the outcome regression is correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias -0.0035 to 0.0066, margin 0.0219, SE ratio 1.3577

pass

double_robustness

continuous_identity_v0_intercept__outcome_correct

positive

intercept coefficient of the identity-link dose MSM (1, a) over the grid, in stratum V = 0: only the outcome regression is correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias -0.0033 to 0.0025, margin 0.0125, SE ratio 1.4455

pass

double_robustness

continuous_identity_v1_a__outcome_correct

positive

dose coefficient of the identity-link dose MSM (1, a) over the grid, in stratum V = 1: only the outcome regression is correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias -0.0017 to 0.0156, margin 0.0377, SE ratio 0.9778

pass

double_robustness

continuous_identity_v1_intercept__outcome_correct

positive

intercept coefficient of the identity-link dose MSM (1, a) over the grid, in stratum V = 1: only the outcome regression is correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias -0.0029 to 0.0060, margin 0.0193, SE ratio 1.1501

pass

double_robustness

continuous_identity_v2_a__outcome_correct

positive

dose coefficient of the identity-link dose MSM (1, a) over the grid, in stratum V = 2: only the outcome regression is correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias -0.0190 to 0.0140, margin 0.0714, SE ratio 0.6073

pass

double_robustness

continuous_identity_v2_intercept__outcome_correct

positive

intercept coefficient of the identity-link dose MSM (1, a) over the grid, in stratum V = 2: only the outcome regression is correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias -0.0103 to 0.0058, margin 0.0348, SE ratio 0.7541

pass

double_robustness

continuous_logit_marginal_a__outcome_correct

positive

dose coefficient of the logit-link dose MSM (1, a) over the grid, marginal: only the outcome regression is correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias -0.0109 to 0.0040, margin 0.0323, SE ratio 1.3104

pass

double_robustness

continuous_logit_marginal_intercept__outcome_correct

positive

intercept coefficient of the logit-link dose MSM (1, a) over the grid, marginal: only the outcome regression is correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias -0.0035 to 0.0047, margin 0.0178, SE ratio 1.3519

pass

double_robustness

continuous_logit_v0_a__outcome_correct

positive

dose coefficient of the logit-link dose MSM (1, a) over the grid, in stratum V = 0: only the outcome regression is correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias -0.0142 to 0.0058, margin 0.0435, SE ratio 1.4313

pass

double_robustness

continuous_logit_v0_intercept__outcome_correct

positive

intercept coefficient of the logit-link dose MSM (1, a) over the grid, in stratum V = 0: only the outcome regression is correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias -0.0052 to 0.0056, margin 0.0234, SE ratio 1.5417

pass

double_robustness

continuous_logit_v1_a__outcome_correct

positive

dose coefficient of the logit-link dose MSM (1, a) over the grid, in stratum V = 1: only the outcome regression is correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias -0.0202 to 0.0076, margin 0.0602, SE ratio 1.3009

pass

double_robustness

continuous_logit_v1_intercept__outcome_correct

positive

intercept coefficient of the logit-link dose MSM (1, a) over the grid, in stratum V = 1: only the outcome regression is correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias -0.0064 to 0.0086, margin 0.0325, SE ratio 1.3576

pass

double_robustness

continuous_logit_v2_a__outcome_correct

positive

dose coefficient of the logit-link dose MSM (1, a) over the grid, in stratum V = 2: only the outcome regression is correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias -0.0576 to -0.0143, margin 0.0939, SE ratio 1.0611

pass

double_robustness

continuous_logit_v2_intercept__outcome_correct

positive

intercept coefficient of the logit-link dose MSM (1, a) over the grid, in stratum V = 2: only the outcome regression is correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias 0.0033 to 0.0247, margin 0.0464, SE ratio 1.2582

pass

double_robustness

v0_a_arm__both_correct

positive

treatment coefficient of the logit MSM (1, a) in stratum V = 0: both the outcome regression and the treatment mechanism are correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias -0.0040 to 0.0154, margin 0.0326, SE ratio 1.0058

pass

double_robustness

v0_a_arm__both_wrong

control

treatment coefficient of the logit MSM (1, a) in stratum V = 0: both nuisances are misspecified

bias interval must fall entirely outside the margin, with the reported standard error still on the scale of the empirical spread

bias 0.1723 to 0.1922, margin 0.0334, SE ratio 0.9974

pass

double_robustness

v0_a_arm__outcome_correct

positive

treatment coefficient of the logit MSM (1, a) in stratum V = 0: only the outcome regression is correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias -0.0089 to 0.0106, margin 0.0328, SE ratio 0.9690

pass

double_robustness

v0_a_arm__treatment_correct

positive

treatment coefficient of the logit MSM (1, a) in stratum V = 0: only the treatment mechanism is correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias -0.0062 to 0.0136, margin 0.0333, SE ratio 1.0265

pass

double_robustness

v1_a_arm__both_correct

positive

treatment coefficient of the logit MSM (1, a) in stratum V = 1: both the outcome regression and the treatment mechanism are correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias -0.0091 to 0.0215, margin 0.0515, SE ratio 1.0028

pass

double_robustness

v1_a_arm__both_wrong

control

treatment coefficient of the logit MSM (1, a) in stratum V = 1: both nuisances are misspecified

bias interval must fall entirely outside the margin, with the reported standard error still on the scale of the empirical spread

bias 0.1743 to 0.2053, margin 0.0520, SE ratio 0.9782

pass

double_robustness

v1_a_arm__outcome_correct

positive

treatment coefficient of the logit MSM (1, a) in stratum V = 1: only the outcome regression is correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias -0.0095 to 0.0212, margin 0.0515, SE ratio 0.9373

pass

double_robustness

v1_a_arm__treatment_correct

positive

treatment coefficient of the logit MSM (1, a) in stratum V = 1: only the treatment mechanism is correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias -0.0110 to 0.0216, margin 0.0547, SE ratio 0.9703

pass

double_robustness

v2_a_arm__both_correct

positive

treatment coefficient of the logit MSM (1, a) in stratum V = 2: both the outcome regression and the treatment mechanism are correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias 0.0066 to 0.0698, margin 0.1061, SE ratio 0.9559

pass

double_robustness

v2_a_arm__both_wrong

control

treatment coefficient of the logit MSM (1, a) in stratum V = 2: both nuisances are misspecified

bias interval must fall entirely outside the margin, with the reported standard error still on the scale of the empirical spread

bias 0.1858 to 0.2450, margin 0.0994, SE ratio 0.9047

pass

double_robustness

v2_a_arm__outcome_correct

positive

treatment coefficient of the logit MSM (1, a) in stratum V = 2: only the outcome regression is correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias 0.0371 to 0.0985, margin 0.1031, SE ratio 0.8261

pass

double_robustness

v2_a_arm__treatment_correct

positive

treatment coefficient of the logit MSM (1, a) in stratum V = 2: only the treatment mechanism is correctly specified

bias interval inside the equivalence margin, with the reported standard error on the scale of the empirical spread

bias 0.0309 to 0.0989, margin 0.1141, SE ratio 0.9176

pass

interval_calibration

logit_marginal_a__correctly_specified

positive

treatment coefficient of the logit MSM (1, a, W), marginal: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9389 to 0.9639, SE ratio 0.9613 to 1.0427

pass

interval_calibration

logit_marginal_a__noise_control

control

treatment coefficient of the logit MSM (1, a, W), marginal: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8131 to 0.8563, SE ratio 0.6819 to 0.7412

pass

interval_calibration

logit_marginal_a__shrunken_se_control

control

treatment coefficient of the logit MSM (1, a, W), marginal: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8073 to 0.8511, SE ratio 0.6729 to 0.7287

pass

interval_calibration

logit_marginal_intercept__correctly_specified

positive

intercept coefficient of the logit MSM (1, a, W), marginal: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9445 to 0.9683, SE ratio 0.9750 to 1.0572

pass

interval_calibration

logit_marginal_intercept__noise_control

control

intercept coefficient of the logit MSM (1, a, W), marginal: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8089 to 0.8525, SE ratio 0.6854 to 0.7432

pass

interval_calibration

logit_marginal_intercept__shrunken_se_control

control

intercept coefficient of the logit MSM (1, a, W), marginal: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8220 to 0.8643, SE ratio 0.6827 to 0.7399

pass

interval_calibration

logit_marginal_w__correctly_specified

positive

baseline-covariate coefficient of the logit MSM (1, a, W), marginal: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9361 to 0.9617, SE ratio 0.9530 to 1.0295

pass

interval_calibration

logit_marginal_w__noise_control

control

baseline-covariate coefficient of the logit MSM (1, a, W), marginal: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8073 to 0.8511, SE ratio 0.6821 to 0.7355

pass

interval_calibration

logit_marginal_w__shrunken_se_control

control

baseline-covariate coefficient of the logit MSM (1, a, W), marginal: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8005 to 0.8449, SE ratio 0.6658 to 0.7212

pass

interval_calibration

logit_v0_a__correctly_specified

positive

treatment coefficient of the logit MSM (1, a, W), in stratum V = 0: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9300 to 0.9569, SE ratio 0.9644 to 1.0471

pass

interval_calibration

logit_v0_a__noise_control

control

treatment coefficient of the logit MSM (1, a, W), in stratum V = 0: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8236 to 0.8657, SE ratio 0.6841 to 0.7426

pass

interval_calibration

logit_v0_a__shrunken_se_control

control

treatment coefficient of the logit MSM (1, a, W), in stratum V = 0: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8136 to 0.8568, SE ratio 0.6752 to 0.7336

pass

interval_calibration

logit_v0_intercept__correctly_specified

positive

intercept coefficient of the logit MSM (1, a, W), in stratum V = 0: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9394 to 0.9643, SE ratio 0.9689 to 1.0521

pass

interval_calibration

logit_v0_intercept__noise_control

control

intercept coefficient of the logit MSM (1, a, W), in stratum V = 0: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8047 to 0.8487, SE ratio 0.6760 to 0.7329

pass

interval_calibration

logit_v0_intercept__shrunken_se_control

control

intercept coefficient of the logit MSM (1, a, W), in stratum V = 0: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8194 to 0.8619, SE ratio 0.6790 to 0.7364

pass

interval_calibration

logit_v0_w__correctly_specified

positive

baseline-covariate coefficient of the logit MSM (1, a, W), in stratum V = 0: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9322 to 0.9586, SE ratio 0.9534 to 1.0308

pass

interval_calibration

logit_v0_w__noise_control

control

baseline-covariate coefficient of the logit MSM (1, a, W), in stratum V = 0: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8121 to 0.8553, SE ratio 0.6788 to 0.7360

pass

interval_calibration

logit_v0_w__shrunken_se_control

control

baseline-covariate coefficient of the logit MSM (1, a, W), in stratum V = 0: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8037 to 0.8478, SE ratio 0.6675 to 0.7207

pass

interval_calibration

logit_v1_a__correctly_specified

positive

treatment coefficient of the logit MSM (1, a, W), in stratum V = 1: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9283 to 0.9555, SE ratio 0.9273 to 1.0105

fail

interval_calibration

logit_v1_a__noise_control

control

treatment coefficient of the logit MSM (1, a, W), in stratum V = 1: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8162 to 0.8591, SE ratio 0.6753 to 0.7359

pass

interval_calibration

logit_v1_a__shrunken_se_control

control

treatment coefficient of the logit MSM (1, a, W), in stratum V = 1: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8037 to 0.8478, SE ratio 0.6498 to 0.7065

pass

interval_calibration

logit_v1_intercept__correctly_specified

positive

intercept coefficient of the logit MSM (1, a, W), in stratum V = 1: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9311 to 0.9578, SE ratio 0.9564 to 1.0350

pass

interval_calibration

logit_v1_intercept__noise_control

control

intercept coefficient of the logit MSM (1, a, W), in stratum V = 1: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8162 to 0.8591, SE ratio 0.7015 to 0.7588

pass

interval_calibration

logit_v1_intercept__shrunken_se_control

control

intercept coefficient of the logit MSM (1, a, W), in stratum V = 1: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.7974 to 0.8421, SE ratio 0.6679 to 0.7242

pass

interval_calibration

logit_v1_w__correctly_specified

positive

baseline-covariate coefficient of the logit MSM (1, a, W), in stratum V = 1: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9417 to 0.9661, SE ratio 0.9498 to 1.0300

pass

interval_calibration

logit_v1_w__noise_control

control

baseline-covariate coefficient of the logit MSM (1, a, W), in stratum V = 1: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8210 to 0.8634, SE ratio 0.6847 to 0.7474

pass

interval_calibration

logit_v1_w__shrunken_se_control

control

baseline-covariate coefficient of the logit MSM (1, a, W), in stratum V = 1: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8058 to 0.8497, SE ratio 0.6649 to 0.7203

pass

interval_calibration

logit_v2_a__correctly_specified

positive

treatment coefficient of the logit MSM (1, a, W), in stratum V = 2: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9289 to 0.9560, SE ratio 0.7818 to 0.9387

fail

interval_calibration

logit_v2_a__noise_control

control

treatment coefficient of the logit MSM (1, a, W), in stratum V = 2: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8037 to 0.8478, SE ratio 0.6035 to 0.6936

pass

interval_calibration

logit_v2_a__shrunken_se_control

control

treatment coefficient of the logit MSM (1, a, W), in stratum V = 2: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8047 to 0.8487, SE ratio 0.5488 to 0.6571

pass

interval_calibration

logit_v2_intercept__correctly_specified

positive

intercept coefficient of the logit MSM (1, a, W), in stratum V = 2: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9389 to 0.9639, SE ratio 0.9592 to 1.0452

pass

interval_calibration

logit_v2_intercept__noise_control

control

intercept coefficient of the logit MSM (1, a, W), in stratum V = 2: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8115 to 0.8549, SE ratio 0.6764 to 0.7334

pass

interval_calibration

logit_v2_intercept__shrunken_se_control

control

intercept coefficient of the logit MSM (1, a, W), in stratum V = 2: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8126 to 0.8558, SE ratio 0.6714 to 0.7321

pass

interval_calibration

logit_v2_w__correctly_specified

positive

baseline-covariate coefficient of the logit MSM (1, a, W), in stratum V = 2: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9541 to 0.9756, SE ratio 0.9623 to 1.0514

pass

interval_calibration

logit_v2_w__noise_control

control

baseline-covariate coefficient of the logit MSM (1, a, W), in stratum V = 2: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8368 to 0.8775, SE ratio 0.7041 to 0.7630

pass

interval_calibration

logit_v2_w__shrunken_se_control

control

baseline-covariate coefficient of the logit MSM (1, a, W), in stratum V = 2: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8373 to 0.8779, SE ratio 0.6741 to 0.7351

pass

interval_calibration

natural_marginal__correctly_specified

positive

cross-fitted natural-course mean with a missing outcome, marginal: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9389 to 0.9639, SE ratio 0.9734 to 1.0577

pass

interval_calibration

natural_marginal__noise_control

control

cross-fitted natural-course mean with a missing outcome, marginal: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8136 to 0.8568, SE ratio 0.6957 to 0.7510

pass

interval_calibration

natural_marginal__shrunken_se_control

control

cross-fitted natural-course mean with a missing outcome, marginal: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8162 to 0.8591, SE ratio 0.6819 to 0.7395

pass

interval_calibration

natural_v0__correctly_specified

positive

cross-fitted natural-course mean with a missing outcome, in stratum V = 0: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9355 to 0.9613, SE ratio 0.9672 to 1.0473

pass

interval_calibration

natural_v0__noise_control

control

cross-fitted natural-course mean with a missing outcome, in stratum V = 0: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8110 to 0.8544, SE ratio 0.6733 to 0.7317

pass

interval_calibration

natural_v0__shrunken_se_control

control

cross-fitted natural-course mean with a missing outcome, in stratum V = 0: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8141 to 0.8572, SE ratio 0.6781 to 0.7340

pass

interval_calibration

natural_v1__correctly_specified

positive

cross-fitted natural-course mean with a missing outcome, in stratum V = 1: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9350 to 0.9608, SE ratio 0.9608 to 1.0439

pass

interval_calibration

natural_v1__noise_control

control

cross-fitted natural-course mean with a missing outcome, in stratum V = 1: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8100 to 0.8534, SE ratio 0.6745 to 0.7343

pass

interval_calibration

natural_v1__shrunken_se_control

control

cross-fitted natural-course mean with a missing outcome, in stratum V = 1: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8152 to 0.8582, SE ratio 0.6716 to 0.7288

pass

interval_calibration

natural_v2__correctly_specified

positive

cross-fitted natural-course mean with a missing outcome, in stratum V = 2: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9294 to 0.9564, SE ratio 0.9752 to 1.0604

pass

interval_calibration

natural_v2__noise_control

control

cross-fitted natural-course mean with a missing outcome, in stratum V = 2: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8115 to 0.8549, SE ratio 0.6809 to 0.7391

pass

interval_calibration

natural_v2__shrunken_se_control

control

cross-fitted natural-course mean with a missing outcome, in stratum V = 2: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8094 to 0.8530, SE ratio 0.6826 to 0.7426

pass

interval_calibration

v0_ate_x05__correctly_specified

positive

incremental contrast of multiplier 0.5 against 1 in stratum V = 0: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9222 to 0.9506, SE ratio 0.9342 to 1.0155

pass

interval_calibration

v0_ate_x05__noise_control

control

incremental contrast of multiplier 0.5 against 1 in stratum V = 0: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8126 to 0.8558, SE ratio 0.6766 to 0.7363

pass

interval_calibration

v0_ate_x05__shrunken_se_control

control

incremental contrast of multiplier 0.5 against 1 in stratum V = 0: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.7969 to 0.8416, SE ratio 0.6540 to 0.7123

pass

interval_calibration

v0_ate_x2__correctly_specified

positive

incremental contrast of multiplier 2 against 1 in stratum V = 0: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9233 to 0.9515, SE ratio 0.9317 to 1.0145

pass

interval_calibration

v0_ate_x2__noise_control

control

incremental contrast of multiplier 2 against 1 in stratum V = 0: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8126 to 0.8558, SE ratio 0.6698 to 0.7249

pass

interval_calibration

v0_ate_x2__shrunken_se_control

control

incremental contrast of multiplier 2 against 1 in stratum V = 0: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.7916 to 0.8368, SE ratio 0.6517 to 0.7081

pass

interval_calibration

v0_ey_natural__correctly_specified

positive

incremental mean at odds multiplier 1 in stratum V = 0: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9451 to 0.9687, SE ratio 0.9786 to 1.0607

pass

interval_calibration

v0_ey_natural__noise_control

control

incremental mean at odds multiplier 1 in stratum V = 0: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8178 to 0.8605, SE ratio 0.6880 to 0.7479

pass

interval_calibration

v0_ey_natural__shrunken_se_control

control

incremental mean at odds multiplier 1 in stratum V = 0: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8110 to 0.8544, SE ratio 0.6853 to 0.7413

pass

interval_calibration

v0_ey_x05__correctly_specified

positive

incremental mean at odds multiplier 0.5 in stratum V = 0: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9411 to 0.9657, SE ratio 0.9699 to 1.0504

pass

interval_calibration

v0_ey_x05__noise_control

control

incremental mean at odds multiplier 0.5 in stratum V = 0: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8136 to 0.8568, SE ratio 0.6763 to 0.7330

pass

interval_calibration

v0_ey_x05__shrunken_se_control

control

incremental mean at odds multiplier 0.5 in stratum V = 0: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8089 to 0.8525, SE ratio 0.6789 to 0.7346

pass

interval_calibration

v0_ey_x2__correctly_specified

positive

incremental mean at odds multiplier 2 in stratum V = 0: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9428 to 0.9670, SE ratio 0.9793 to 1.0618

pass

interval_calibration

v0_ey_x2__noise_control

control

incremental mean at odds multiplier 2 in stratum V = 0: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8241 to 0.8662, SE ratio 0.6955 to 0.7533

pass

interval_calibration

v0_ey_x2__shrunken_se_control

control

incremental mean at odds multiplier 2 in stratum V = 0: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8157 to 0.8586, SE ratio 0.6852 to 0.7441

pass

interval_calibration

v1_ate_x05__correctly_specified

positive

incremental contrast of multiplier 0.5 against 1 in stratum V = 1: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9400 to 0.9648, SE ratio 0.9681 to 1.0462

pass

interval_calibration

v1_ate_x05__noise_control

control

incremental contrast of multiplier 0.5 against 1 in stratum V = 1: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8110 to 0.8544, SE ratio 0.6885 to 0.7460

pass

interval_calibration

v1_ate_x05__shrunken_se_control

control

incremental contrast of multiplier 0.5 against 1 in stratum V = 1: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8052 to 0.8492, SE ratio 0.6785 to 0.7334

pass

interval_calibration

v1_ate_x2__correctly_specified

positive

incremental contrast of multiplier 2 against 1 in stratum V = 1: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9394 to 0.9643, SE ratio 0.9718 to 1.0513

pass

interval_calibration

v1_ate_x2__noise_control

control

incremental contrast of multiplier 2 against 1 in stratum V = 1: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8178 to 0.8605, SE ratio 0.6865 to 0.7453

pass

interval_calibration

v1_ate_x2__shrunken_se_control

control

incremental contrast of multiplier 2 against 1 in stratum V = 1: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8063 to 0.8501, SE ratio 0.6801 to 0.7361

pass

interval_calibration

v1_ey_natural__correctly_specified

positive

incremental mean at odds multiplier 1 in stratum V = 1: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9389 to 0.9639, SE ratio 0.9570 to 1.0380

pass

interval_calibration

v1_ey_natural__noise_control

control

incremental mean at odds multiplier 1 in stratum V = 1: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.7990 to 0.8435, SE ratio 0.6673 to 0.7239

pass

interval_calibration

v1_ey_natural__shrunken_se_control

control

incremental mean at odds multiplier 1 in stratum V = 1: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8084 to 0.8520, SE ratio 0.6703 to 0.7262

pass

interval_calibration

v1_ey_x05__correctly_specified

positive

incremental mean at odds multiplier 0.5 in stratum V = 1: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9350 to 0.9608, SE ratio 0.9653 to 1.0474

pass

interval_calibration

v1_ey_x05__noise_control

control

incremental mean at odds multiplier 0.5 in stratum V = 1: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8262 to 0.8681, SE ratio 0.7051 to 0.7668

pass

interval_calibration

v1_ey_x05__shrunken_se_control

control

incremental mean at odds multiplier 0.5 in stratum V = 1: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8094 to 0.8530, SE ratio 0.6760 to 0.7327

pass

interval_calibration

v1_ey_x2__correctly_specified

positive

incremental mean at odds multiplier 2 in stratum V = 1: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9339 to 0.9600, SE ratio 0.9453 to 1.0272

pass

interval_calibration

v1_ey_x2__noise_control

control

incremental mean at odds multiplier 2 in stratum V = 1: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.7901 to 0.8354, SE ratio 0.6583 to 0.7127

pass

interval_calibration

v1_ey_x2__shrunken_se_control

control

incremental mean at odds multiplier 2 in stratum V = 1: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8105 to 0.8539, SE ratio 0.6622 to 0.7208

pass

interval_calibration

v2_ate_x05__correctly_specified

positive

incremental contrast of multiplier 0.5 against 1 in stratum V = 2: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9344 to 0.9604, SE ratio 0.9546 to 1.0359

pass

interval_calibration

v2_ate_x05__noise_control

control

incremental contrast of multiplier 0.5 against 1 in stratum V = 2: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8084 to 0.8520, SE ratio 0.6716 to 0.7303

pass

interval_calibration

v2_ate_x05__shrunken_se_control

control

incremental contrast of multiplier 0.5 against 1 in stratum V = 2: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8031 to 0.8473, SE ratio 0.6670 to 0.7256

pass

interval_calibration

v2_ate_x2__correctly_specified

positive

incremental contrast of multiplier 2 against 1 in stratum V = 2: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9305 to 0.9573, SE ratio 0.9518 to 1.0334

pass

interval_calibration

v2_ate_x2__noise_control

control

incremental contrast of multiplier 2 against 1 in stratum V = 2: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8089 to 0.8525, SE ratio 0.6656 to 0.7232

pass

interval_calibration

v2_ate_x2__shrunken_se_control

control

incremental contrast of multiplier 2 against 1 in stratum V = 2: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8026 to 0.8468, SE ratio 0.6652 to 0.7231

pass

interval_calibration

v2_ey_natural__correctly_specified

positive

incremental mean at odds multiplier 1 in stratum V = 2: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9322 to 0.9586, SE ratio 0.9700 to 1.0550

pass

interval_calibration

v2_ey_natural__noise_control

control

incremental mean at odds multiplier 1 in stratum V = 2: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8026 to 0.8468, SE ratio 0.6595 to 0.7196

pass

interval_calibration

v2_ey_natural__shrunken_se_control

control

incremental mean at odds multiplier 1 in stratum V = 2: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8084 to 0.8520, SE ratio 0.6783 to 0.7381

pass

interval_calibration

v2_ey_x05__correctly_specified

positive

incremental mean at odds multiplier 0.5 in stratum V = 2: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9311 to 0.9578, SE ratio 0.9665 to 1.0532

pass

interval_calibration

v2_ey_x05__noise_control

control

incremental mean at odds multiplier 0.5 in stratum V = 2: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.7974 to 0.8421, SE ratio 0.6692 to 0.7266

pass

interval_calibration

v2_ey_x05__shrunken_se_control

control

incremental mean at odds multiplier 0.5 in stratum V = 2: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8147 to 0.8577, SE ratio 0.6761 to 0.7367

pass

interval_calibration

v2_ey_x2__correctly_specified

positive

incremental mean at odds multiplier 2 in stratum V = 2: both nuisances are correctly specified

SE ratio and coverage intervals both inside their calibration bands

coverage 0.9300 to 0.9569, SE ratio 0.9671 to 1.0518

pass

interval_calibration

v2_ey_x2__noise_control

control

incremental mean at odds multiplier 2 in stratum V = 2: a declared scale of independent noise is added to each estimate

the SE-ratio interval must fall below the calibration band

coverage 0.8247 to 0.8667, SE ratio 0.6905 to 0.7493

pass

interval_calibration

v2_ey_x2__shrunken_se_control

control

incremental mean at odds multiplier 2 in stratum V = 2: the reported standard errors are multiplied by a declared factor below one

the SE-ratio interval must fall below the calibration band

coverage 0.8094 to 0.8530, SE ratio 0.6781 to 0.7364

pass

simultaneous_coverage

ipsi_strata__pointwise_joint_control

control

the five marginal and fifteen stratum incremental parameters of one fit: the pointwise 95% intervals of the same fits, read jointly

joint coverage upper endpoint must fall below the nominal rate

joint coverage 0.6057 to 0.6616

pass

simultaneous_coverage

ipsi_strata__simultaneous_band

positive

the five marginal and fifteen stratum incremental parameters of one fit: the max-t multiplier band over every estimand the law reports, from the same-row centered influence curves

joint coverage interval inside the calibration coverage band

joint coverage 0.9261 to 0.9538

pass

stratum_targeting_necessity

v0_ey_x2__marginal_fluctuation

control

incremental mean at odds multiplier 2 in stratum V = 0: the same outcome regression in the unstratified incremental fit, its targeted mixture averaged inside the stratum

bias interval must fall entirely outside the margin

bias 0.0998 to 0.1017, margin 0.0031

pass

stratum_targeting_necessity

v0_ey_x2__stratified

positive

incremental mean at odds multiplier 2 in stratum V = 0: the stratified fit with an outcome regression that omits the stratum, so the per-stratum score blocks do all the adjusting

bias interval inside the equivalence margin

bias -0.0011 to 0.0014, margin 0.0042

pass

stratum_targeting_necessity

v2_ey_x2__marginal_fluctuation

control

incremental mean at odds multiplier 2 in stratum V = 2: the same outcome regression in the unstratified incremental fit, its targeted mixture averaged inside the stratum

bias interval must fall entirely outside the margin

bias -0.1583 to -0.1565, margin 0.0030

pass

stratum_targeting_necessity

v2_ey_x2__stratified

positive

incremental mean at odds multiplier 2 in stratum V = 2: the stratified fit with an outcome regression that omits the stratum, so the per-stratum score blocks do all the adjusting

bias interval inside the equivalence margin

bias -0.0015 to 0.000807, margin 0.0039

pass

targeting_necessity

v0_a__targeted

positive

treatment coefficient of the logit MSM (1, a, W) in stratum V = 0: the estimator fluctuates a misspecified outcome model, so targeting does all the adjusting

bias interval inside the equivalence margin

bias -0.0062 to 0.0141, margin 0.0342

pass

targeting_necessity

v0_a__untargeted

control

treatment coefficient of the logit MSM (1, a, W) in stratum V = 0: the identical fit with every fluctuation step removed

bias interval must fall entirely outside the margin

bias -0.2498 to -0.2345, margin 0.0257

pass

targeting_necessity

v1_a__targeted

positive

treatment coefficient of the logit MSM (1, a, W) in stratum V = 1: the estimator fluctuates a misspecified outcome model, so targeting does all the adjusting

bias interval inside the equivalence margin

bias -0.0021 to 0.0305, margin 0.0546

pass

targeting_necessity

v1_a__untargeted

control

treatment coefficient of the logit MSM (1, a, W) in stratum V = 1: the identical fit with every fluctuation step removed

bias interval must fall entirely outside the margin

bias -0.2498 to -0.2345, margin 0.0257

pass

The property grid has six families.

family

what it measures

interval_calibration

the fifteen stratum incremental parameters; the logit MSM \((1, a, W)\), marginal and in each stratum; and the cross-fitted natural-course mean, marginal and in each stratum. Each cell has a shrunken-SE control and a noise control

simultaneous_coverage

the band over the twenty incremental parameters of one fit

stratum_targeting_necessity

the stratified incremental fit against the unstratified fit’s mixture inside a stratum, with an outcome regression that omits \(V\)

targeting_necessity

the stratified logit-MSM slope against the untargeted stratum projection of the same initial regression

double_robustness

the logit MSM \((1, a)\) in each stratum under four nuisance configurations, and the dose MSM coefficients with a correct outcome regression

The robustness family fits \((1, a)\), not \((1, a, W)\). Inside a stratum the logit model \((1, a, W)\) contains the outcome regression, so a fit with both nuisances wrong stays within 0.5 SD of the truth, and its control could not fail. The dose cells are robustness cells and not calibration cells. The package fits the dose density with bins, which is not the law’s density, so no result predicts a calibrated standard error.

Two positive cells are red, and both measure the logit-MSM slope: interval_calibration/logit_v1_a__correctly_specified and logit_v2_a__correctly_specified. Their SE ratios are 0.967 and 0.862, and the lower ends of their intervals are 0.927 and 0.782 against a floor of 0.93. Both cover nominally. Stratum 1 holds about 600 of the 2,000 rows, and stratum 2 about 400.

The owner X8-logit-small-stratum in the roadmap records the diagnosis. A declared diagnostic read stratum 2 only. It fitted the shipped unstratified logit MSM on samples of stratum 2’s size from the law given \(V = 2\). That fit under-reports as well: 0.896, against the stratified fit’s 0.867 on fresh draws. At four times the size the two read 0.997 and 1.006.

No diagnostic reads stratum 1, whose interval misses the floor by 0.003. The study declared gated and moved to reporting before a re-run at the same seeds, which its declaration allows for a finite-sample red with no defect.

Measured values and declared margins#

quantity

value

source

replicates

1600

paired replications

n

2000

observations per primary replication

independent_tests_passed

40

truth tests passing

independent_tests_total

40

truth tests reported

paired_tests_passed

20

paired comparisons passing

paired_tests_total

20

paired comparisons reported

property_cells_passed

129

property cells passing

property_cells_total

131

property cells reported

max_standardized_bias

0.0634

largest primary standardized bias

min_coverage

0.9350

lowest primary coverage

max_margin_utilization

0.7097

largest paired similarity-margin share

margin:confidence_level

0.9900

Monte Carlo confidence level

margin:alpha

0.0500

nominal test size

margin:nominal_coverage

0.9500

nominal interval coverage

margin:bootstrap_replicates

10000

bootstrap replications

margin:targeting_displacement

0.2500

necessity displacement threshold in standardized units

margin:standardized_bias

0.2500

standardized-bias margin

margin:union_model_se_lower

0.1000

union-model SE-ratio screen, lower limit

margin:union_model_se_upper

10

union-model SE-ratio screen, upper limit

margin:coverage_floor

0.9000

primary coverage floor

margin:over_coverage_ceiling

0.9900

descriptive overcoverage threshold

margin:se_ratio_sanity_lower

0.8000

primary SE-ratio lower screen

margin:se_ratio_sanity_upper

1.2000

primary SE-ratio upper screen

margin:calibration_se_ratio_lower

0.9300

calibration SE-ratio lower bound

margin:calibration_se_ratio_upper

1.0700

calibration SE-ratio upper bound

margin:calibration_coverage_lower

0.9200

calibration coverage lower bound

margin:calibration_coverage_upper

0.9800

calibration coverage upper bound

margin:type_i_ceiling

0.1000

type-I upper bound

margin:paired_difference

0.1500

paired similarity margin in pooled SDs

margin:rmse_noninferiority

1.1000

RMSE-ratio noninferiority bound

margin:coverage_noninferiority

-0.0250

coverage-difference noninferiority bound

margin:calibration_noninferiority

0.0500

calibration-excess noninferiority bound

margin:minimum_power

0.8000

minimum power lower bound

margin:root_n_slope

-0.5000

expected root-n slope

margin:root_n_slope_lower

-0.6250

root-n slope lower bound

margin:root_n_slope_upper

-0.3750

root-n slope upper bound

margin:excluded_slope

-0.2500

slower rate the interval must exclude

margin:shrunken_se_factor

0.7000

negative-control SE multiplier

bound:ate_ipsi[odds x0.5 vs natural course][V=0]_standard_error

0.0050

exact L1 efficiency-bound standard error at primary n

bound:ate_ipsi[odds x0.5 vs natural course][V=1]_standard_error

0.0053

exact L1 efficiency-bound standard error at primary n

bound:ate_ipsi[odds x0.5 vs natural course][V=2]_standard_error

0.0043

exact L1 efficiency-bound standard error at primary n

bound:ate_ipsi[odds x0.5 vs natural course]_standard_error

0.0031

exact L1 efficiency-bound standard error at primary n

bound:ate_ipsi[odds x2 vs natural course][V=0]_standard_error

0.0050

exact L1 efficiency-bound standard error at primary n

bound:ate_ipsi[odds x2 vs natural course][V=1]_standard_error

0.0058

exact L1 efficiency-bound standard error at primary n

bound:ate_ipsi[odds x2 vs natural course][V=2]_standard_error

0.0050

exact L1 efficiency-bound standard error at primary n

bound:ate_ipsi[odds x2 vs natural course]_standard_error

0.0032

exact L1 efficiency-bound standard error at primary n

bound:ey_ipsi[natural course][V=0]_standard_error

0.0158

exact L1 efficiency-bound standard error at primary n

bound:ey_ipsi[natural course][V=1]_standard_error

0.0180

exact L1 efficiency-bound standard error at primary n

bound:ey_ipsi[natural course][V=2]_standard_error

0.0163

exact L1 efficiency-bound standard error at primary n

bound:ey_ipsi[natural course]_standard_error

0.0106

exact L1 efficiency-bound standard error at primary n

bound:ey_ipsi[odds x0.5][V=0]_standard_error

0.0166

exact L1 efficiency-bound standard error at primary n

bound:ey_ipsi[odds x0.5][V=1]_standard_error

0.0198

exact L1 efficiency-bound standard error at primary n

bound:ey_ipsi[odds x0.5][V=2]_standard_error

0.0182

exact L1 efficiency-bound standard error at primary n

bound:ey_ipsi[odds x0.5]_standard_error

0.0113

exact L1 efficiency-bound standard error at primary n

bound:ey_ipsi[odds x2][V=0]_standard_error

0.0164

exact L1 efficiency-bound standard error at primary n

bound:ey_ipsi[odds x2][V=1]_standard_error

0.0176

exact L1 efficiency-bound standard error at primary n

bound:ey_ipsi[odds x2][V=2]_standard_error

0.0154

exact L1 efficiency-bound standard error at primary n

bound:ey_ipsi[odds x2]_standard_error

0.0106

exact L1 efficiency-bound standard error at primary n

Limits#

  • The study covers two finite-support laws with one three-level stratum, and one continuous-dose law with the same strata.

  • The incremental and MSM fits are in sample. The cross-fitted forms of these targets are not measured here.

  • The dose fits use the package’s binned density on six bins. They publish no calibration cell and no band.

  • The MSM and natural-course targets have no stratified comparator, so only the truth measures them.

  • targeting_scheme="fold" and cv_evaluation=True refuse strata, so neither is measured.

Reproduction#

The fixture README, manifest, replications, paired decisions, and property results carry the protocol, provenance, and every published row.