Cited by 55Advanced Causal Inference TechniquesEvaluation and Performance AssessmentMeta-analysis and systematic reviews

Twenty-six assumptions that have to be met if single random assignment experiments are to warrant “gold standard” status: A commentary on Deaton and Cartwright

Cook, Thomas D.·2018·Social Science & Medicine

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Crossref · 10.1016/j.socscimed.2018.04.031

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  • Even though experiments are among the methods that have experienced replication problems, and even though they have very demanding requirements and assumptions, properly done experiments are less subject to some of the methodological limits of observational statistical studies.

    “Even though experiments are among the methods that have experienced replication problems, and even though they have very demanding requirements and assumptions (especially field experiments: Cook, 2018), properly done experiments are less subject to some of the methodological limits of observational statistical studies.”

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Authors
Cook, T. D.
Affiliations
Northwestern University (US)
Corresponding author
Cook, Thomas D.
Venue
Social Science & Medicine
Publisher
Elsevier BV
Published
2018-08
Volume
210
Pages
37-40
ISSN
0277-9536 (ISSN-L)
OpenAlex
W2800289677
Cited by
55
References
1
Citations by year
2026: 2 · 2025: 8 · 2024: 6 · 2023: 9 · 2022: 2 · 2021: 1 · 2020: 22 · 2019: 3 · 2018: 2
FWCI
5.83
Type
journal article
Language
en
Open access
closed
Locations
  • Social Science & Medicine (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Evaluation and Performance Assessment
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Keywords
causal inference, random assignment, gold standard, confounder control, propensity score matching, instrumental variables, regression discontinuity design, difference-in-differences, threats to validity, internal validity, generalizability, statistical power, measurement quality, education and health, interdisciplinary methodology
MeSH terms
Research Design, Randomized Controlled Trials as Topic, Comprehension

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