Descriptive data study
Question and data in, a checked description of the data out: the sample and its filters, summary statistics, distributions and associations, figures re-read from the data. A data check stops the run on missing units, duplicate rows, unexplained gaps or missing coverage before anything is computed.
Where it sits
left: what it builds on · right: what builds on it · pale: exampleBy e2er authors
How studies reach it
No published study reaches it yet.
Disciplines it reaches
No study reaches it yet.
Solid: published studies. Light: examples.
Computed from the records on this site: what each study, template and specialist names as used, which study extends which, and who authored what. 0 studies in total.
- Input
- A research question and data
- Output
- A checked description of the data (the sample, summary statistics, distributions, associations, figures re-read from the data) as a draft paper with a dossier
- At the end
- When any run ends, e2er builds the PDF, writes the audit trail and the structured export, and pushes to GitHub if you set that up.
Sources
- Methods
John D. Emerson and Graham A. Colditz. Use of Statistical Analysis in The New England Journal of Medicine. New England Journal of Medicine 309(12), 709-713.
David Freedman and Persi Diaconis. On the histogram as a density estimator: L2 theory. Zeitschrift für Wahrscheinlichkeitstheorie und Verwandte Gebiete 57(4), 453-476.
Rob J. Hyndman and Yanan Fan. Sample Quantiles in Statistical Packages. The American Statistician 50(4), 361-365.
Charles Spearman. The Proof and Measurement of Association between Two Things. The American Journal of Psychology 15(1), 72-101.
Roderick Little and Donald Rubin. Statistical Analysis with Missing Data (3rd edition). Wiley.
Hadley Wickham. Tidy Data. Journal of Statistical Software 59(10).
Steps
Greyed steps do not run in the selected mode.
- 1 your reviewDesign reviewThe researcher reads the plan, the literature and the declared data before anything is loaded.
- 2 checkData check: units, duplicates, missing valuesAfter the data analyst, before the analysis: units, duplicates, missing values and coverage of every declared table (src/core/pipeline/data_quality.py); writes data_quality.md.
- 3 checkFigures re-read before the draftThe figures re-read from the data once the analysis is done, before the paper drafter is dispatched.
- 4 specialistsDesign, data, estimation and draft
- 5 specialistsImprove until it stops getting better
- 6 checkEstimation checkThe results file held to the descriptive contract.
- 7 checkFigures re-read from the dataEvery figure re-read from the data or results it names.
- 8 your reviewDraft reviewThe researcher reads the draft before the reviewers.
- 9 specialistsSelf-critique
- 10 specialists, parallel
- 11 reviewers, parallelReview panel
- 12 specialistsRevision
- 13 specialistsReplication package
Technical details
Template id descriptive-study · file pipelines/descriptive-study.toml, checked against pipeline.schema.json.
| Step | Id in the template file | Specialists |
|---|---|---|
| 1. Design review | review_design | |
| 2. Data check: units, duplicates, missing values | data_quality_gate | |
| 3. Figures re-read before the draft | figures_before_draft | |
| 4. Design, data, estimation and draft | initial | idea_developer, literature_scanner, data_architect, identification_strategist, econometrics_specialist, data_analyst, paper_drafter |
| 5. Improve until it stops getting better | iterative | |
| 6. Estimation check | estimation_gate | |
| 7. Figures re-read from the data | figure_gate | |
| 8. Draft review | review_draft | |
| 9. Self-critique | self_attack | self_attacker |
| 10. Polish | polish | polish_numerics, polish_bibliography |
| 11. Review panel | review | data_reviewer, methods_reviewer, plausibility_reviewer, literature_reviewer, writing_reviewer |
| 12. Revision | revision | revisor, patch_revisor |
| 13. Replication package | replication | replication_packager |
At the end (finalize): compile, audit_export, github_push, structured_export. Modes: single_pass, iterative.
More
Description
Data model- Discipline
- General
- Method family
- Empirical (quantitative)
- Design
- not specified
- Research stage
- ReviewRevision and editingReplication
- Authors
- e2er authors (Software, Methodology)
- Usage
- not used in published research yet
- Source
- e2er repository · pipelines/descriptive-study.toml · @d8fd8ab
- Record
- template:descriptive-study · JSON
Solid tags are declared by the source or mapped from its terms; dashed tags are inferred by a published rule. Hover a tag for its provenance.
Versions and evaluations
One version, unreleasedOne version so far: pipelines/descriptive-study.toml in e2er 0.16.1. No evaluation records exist yet.
Connectors this template can use
What a run of this template can reach outside your machine, and what each sends out.
Checks on this template
- ✓Output contracts · Every step produced the artifact it declared, in the declared form
Required of every template. - ✓Execution reliability · Analysis code ran and wrote a parseable, non-empty result
Required of every template. - ○Numbers · Every number in tables and text matches the output of executed code
Proposed. Proposed for the floor; runs log it but may not block on it. - ○Citations · Every reference resolves to an existing publication via OpenAlex, Semantic Scholar or Crossref
Proposed. Proposed for the floor; runs log it but may not block on it. - ○Verbatim passages · Every claim about a source points to a passage found word for word in that source
Proposed. Proposed for the floor; runs log it but may not block on it.
Runs of this template
No runs yet.
Use it
Install e2er as described on the Install page, then start a run:
e2er run "<your research question>" --template descriptive-studyFrom e2er 0.16.1. Get started goes from install to publish.
On e2er.org
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Discussion
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