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Paper Citation Record · LEDGER

A Law of Iterated Expectation Primer for Causal Inference

As of 14 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2606.20078.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2606.20078 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-26T15:03:11.522485Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

13 of 13 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved13
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 48e329c5-e3af-407b-8315-0ed864edd963 · outbound

This paper cites A New Approach to Causal Inference in Mortality Studies with a Sustained Exposure Period–Application to Control of the Healthy Worker Survivor Effect.Mathe- matical Modelling.

A Law of Iterated Expectation Primer for Causal Inference A New Approach to Causal Inference in Mortality Studies with a Sustained Exposure Period–Application to Control of the Healthy Worker Survivor Effect.Mathe- matical Modelling

Reference 1

Resolution
unresolved
no resolver link, observed 2026-06-26T15:03:11.522485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T15:03:11.522485Z digest=sha256:5c9bc7c44e7b0782e4c2998efef946d98963c077ad579fdcebd1235df5c3ea5c

Observation 7d8277b3-7782-47fd-bbfa-7d7aa8840fdc · outbound

This paper cites Springer.

A Law of Iterated Expectation Primer for Causal Inference Springer

Reference 2

Resolution
unresolved
no resolver link, observed 2026-06-26T15:03:11.522485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T15:03:11.522485Z digest=sha256:80c8f637e469fcef03e1e4b11d02d5e42476a362f27a16dd725083db07a59147

Observation 487e8964-b1da-4932-a045-95f7e7c48f61 · outbound

This paper cites Cambridge University Press.

A Law of Iterated Expectation Primer for Causal Inference Cambridge University Press

Reference 3

Resolution
unresolved
no resolver link, observed 2026-06-26T15:03:11.522485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T15:03:11.522485Z digest=sha256:5e1a7e09aac8867303a2ba578f898ec0210e4be4ae84158eddb722af0737fba9

Observation 8534b34b-da9b-44fb-867e-b22fa58365b1 · outbound

This paper cites Marginal Structural Models as a Tool for Standardization.Epi- demiol.

A Law of Iterated Expectation Primer for Causal Inference Marginal Structural Models as a Tool for Standardization.Epi- demiol

Reference 4

Resolution
unresolved
no resolver link, observed 2026-06-26T15:03:11.522485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T15:03:11.522485Z digest=sha256:13605200701f89fff1b642c444973174d4fa8f7778009ba754756f71fe84e5b6

Observation fd546410-3f10-4dee-bb0a-63a4cb10abd2 · outbound

This paper cites CRC Press.

A Law of Iterated Expectation Primer for Causal Inference CRC Press

Reference 5

Resolution
unresolved
no resolver link, observed 2026-06-26T15:03:11.522485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T15:03:11.522485Z digest=sha256:58999565f2c9dee07e6a227e0907360aa1588976cbfed94a06f18f99ae37a533

Observation 21df4a0c-54b5-4fc4-9e39-7c32a25468fa · outbound

This paper cites Defining and Identifying Average Treatment Effects.Amer- ican journal of epidemiology.

A Law of Iterated Expectation Primer for Causal Inference Defining and Identifying Average Treatment Effects.Amer- ican journal of epidemiology

Reference 6

Resolution
unresolved
no resolver link, observed 2026-06-26T15:03:11.522485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T15:03:11.522485Z digest=sha256:91e4c702e623f11c80f0b7b3404a486877c566088c20879841daaa10f002e96d

Observation 4106b665-042d-46a9-a2c3-ea4ab3ed9334 · outbound

This paper cites Concerning the consistency assumption in causal inference.Epidemiol.

A Law of Iterated Expectation Primer for Causal Inference Concerning the consistency assumption in causal inference.Epidemiol

Reference 7

Resolution
unresolved
no resolver link, observed 2026-06-26T15:03:11.522485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T15:03:11.522485Z digest=sha256:e6e00884f5df828fa1e05a245086cf7ff795eacf95612b58f910ea37e1b8b31a

Observation d7923acc-173a-4828-b3fc-ecd1dd9e707f · outbound

This paper cites Parametric G-Formula Implementations for Causal Survival Analyses.Biometrics.

A Law of Iterated Expectation Primer for Causal Inference Parametric G-Formula Implementations for Causal Survival Analyses.Biometrics

Reference 8

Resolution
unresolved
no resolver link, observed 2026-06-26T15:03:11.522485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T15:03:11.522485Z digest=sha256:5d1e7950dc0925a9b0ae9529c22f017ccbb73dd73825897a5f83c27bee95e17d

Observation 5934d23c-aab8-46ed-925d-fe4183ef3a50 · outbound

This paper cites An introduction to g methods.International journal of epidemiology.

A Law of Iterated Expectation Primer for Causal Inference An introduction to g methods.International journal of epidemiology

Reference 9

Resolution
unresolved
no resolver link, observed 2026-06-26T15:03:11.522485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T15:03:11.522485Z digest=sha256:98c946131957d6568e417ec8be725419bf05b35f3f2fa1432532d4bbcee37023

Observation d65dd16e-23e2-466d-ab9b-0a42d54204be · outbound

This paper cites Using Longitudinal Tar- geted Maximum Likelihood Estimation in Complex Settings with Dynamic Interventions.

A Law of Iterated Expectation Primer for Causal Inference Using Longitudinal Tar- geted Maximum Likelihood Estimation in Complex Settings with Dynamic Interventions

Reference 10

Resolution
unresolved
no resolver link, observed 2026-06-26T15:03:11.522485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T15:03:11.522485Z digest=sha256:9c3da861b9f69102440de1c80f29a8ceee6a5471f6dcd153870fd64914cbde88

Observation d66250ff-52bd-4f2f-8f13-49557567ce83 · outbound

This paper cites Analysis of occupational asbestos expo- sure and lung cancer mortality using the g formula.American journal of epidemiology.

A Law of Iterated Expectation Primer for Causal Inference Analysis of occupational asbestos expo- sure and lung cancer mortality using the g formula.American journal of epidemiology

Reference 11

Resolution
unresolved
no resolver link, observed 2026-06-26T15:03:11.522485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T15:03:11.522485Z digest=sha256:9b514cf6ba7abb1bad9c613ff5dbcd20699970d5b28c39f711b094964e53b17a

Observation a1cc39fa-f307-4083-81cd-a3f214c019f2 · outbound

This paper cites 2021; 174:595–601.

A Law of Iterated Expectation Primer for Causal Inference 2021; 174:595–601

Reference 12

Resolution
unresolved
no resolver link, observed 2026-06-26T15:03:11.522485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T15:03:11.522485Z digest=sha256:8378b41c6b9e74fc361cb1bd85788d73a9d3bbeef5397b647c8904aba6ec890e

Observation 743430e7-4713-41c4-a8a6-c5f67c7669f3 · outbound

This paper cites nu”). Informally, this reference measure is a rule for assigning “sizes.

A Law of Iterated Expectation Primer for Causal Inference nu”). Informally, this reference measure is a rule for assigning “sizes

Reference 13

Resolution
unresolved
no resolver link, observed 2026-06-26T15:03:11.522485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T15:03:11.522485Z digest=sha256:726aabbcaa05696ab4872536212e5a25647603c48383bd5e1a85dd65cb81c25e

Pith citing papers

No inbound Pith citation observations are available.