Cited by 1,150Advanced Causal Inference TechniquesStatistical Methods in EpidemiologyOptimal Experimental Design Methods

Design of Observational Studies

Rosenbaum, Paul R.·2010·Springer Series in Statistics

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Crossref · 10.1007/978-1-4419-1213-8

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12 of 12 references verified0 citation errors · 0 not checkable

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  • The propensity score has a balancing property: if customers have the same propensity score, then the difference in their risk characteristics is independent of the assigned treatment.

    “Interestingly, this score has a balancing property that states that if customers have the same propensity score, then the difference in their risk characteristics is independent of the assigned treatment, or 𝑇 𝑖 ⟂ 𝑿 𝑖 |𝜋(𝑡 𝑐 , 𝑿 𝑖 ) ∀𝑐 ∈ {1, … , 𝐶} (Guo & Fraser, 2009;Imbens, 2004;Rosenbaum, 2010).”

    From Customer price sensitivities in competitive insurance markets (2022) · cites this paper as Rosenbaum, 2010

  • Quasi-experimental methods such as instrumental variables and regression discontinuity designs allow for causal conclusions from observational snapshots when investigators make strong, explicit assumptions and articulate a credible identification strategy.

    “We recognize, of course, that quasi-experimental methods such as instrumental variables and regression discontinuity designs allow for causal conclusions to be drawn from observational snapshots when investigators make strong, explicit assumptions and articulate a credible identification strategy 27-30 .”

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Authors
Rosenbaum, P. R.
Affiliations
University of Pennsylvania (US)
Corresponding author
Rosenbaum, Paul R.
Venue
Springer Series in Statistics
Published
2010
ISSN
0172-7397 (ISSN-L)
OpenAlex
W253646976
Cited by
1,150
References
12
Citations by year
2026: 33 · 2025: 72 · 2024: 58 · 2023: 58 · 2022: 73 · 2021: 115 · 2020: 108 · 2019: 71 · 2018: 73 · 2017: 68 · 2016: 75 · 2015: 85 · 2014: 84 · 2013: 58 · 2012: 55
FWCI
6.61
Type
book
Language
en
Open access
closed
Locations
  • Springer series in statistics (publishedVersion)
  • CERN Document Server (European Organization for Nuclear Research) (submittedVersion)
  • Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)) (submittedVersion)
Funders
National Science Foundation
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, research design, causal inference, statistical inference, confounding

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