Cited by 484Advanced Causal Inference TechniquesStatistical Methods in EpidemiologyOptimal Experimental Design Methods

Observational Studies

Rosenbaum, Paul R.·2002·Springer Series in Statistics

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Crossref · 10.1007/978-1-4757-3692-2_1

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  • It is not possible to directly test whether the unconfoundedness condition is satisfied; a sensitivity analysis following Rosenbaum's (2002) bounding approach helps provide insight.

    “Even though it is not possible to directly test whether the unconfoundedness condition is satisfied or not, a sensitivity analysis following, for example, Rosenbaum's (2002) bounding approach helps to provide insight.”

    From Does shelter assistance reduce poverty in Afghanistan (2015) · cites this paper as Rosenbaum's (2002)

  • To assess the robustness of our results, we conduct a sensitivity analysis following Rosenbaum's (2002) bounding approach.

    “To assess the robustness of our results in this regard we conduct a sensitivity analysis following Rosenbaum's (2002) bounding approach.”

    From Does shelter assistance reduce poverty in Afghanistan (2015) · cites this paper as Rosenbaum's (2002)

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Authors
Rosenbaum, P. R.
Affiliations
University of Pennsylvania (US)
Corresponding author
Rosenbaum, Paul R.
Venue
Springer Series in Statistics
Published
2002
Pages
1-17
ISSN
0172-7397 (ISSN-L)
OpenAlex
W4234209132
Cited by
484
References
0
Citations by year
2026: 8 · 2025: 21 · 2024: 22 · 2023: 26 · 2022: 21 · 2021: 41 · 2020: 35 · 2019: 44 · 2018: 36 · 2017: 37 · 2016: 24 · 2015: 22 · 2014: 25 · 2013: 18 · 2012: 23
FWCI
17.44
Type
book chapter
Language
en
Open access
closed
Locations
Springer series in statistics (publishedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Optimal Experimental Design Methods
Keywords
observational studies, causal inference, smoking and lung cancer, history of statistics

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