Design sensitivity in observational studies

By Paul R. Rosenbaum. 2004

152 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/1793f31e67f37797ae7f5dc0dcf2763bd1bfa7fd

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Management Science and Operations Research

1. Qingyuan Zhao
2. Dylan S. Small
3. Paul R. Rosenbaum
4. J. Hsu
5. Ruth Heller
6. Christopher S. Armstrong
7. W. Guay
8. José R. Zubizarreta

In Statistics and Probability

1. Qingyuan Zhao
2. Dylan S. Small
3. J. Hsu
4. José R. Zubizarreta
5. Paul R. Rosenbaum
6. Ruth Heller
7. Christopher S. Armstrong
8. W. Guay

Citations in the corpus

• Split Samples and Design Sensitivity in Observational Studies (2009, methodology): “see Rosenbaum (2004, 2005) and Small and Rosenbaum (2008).”
• War and Wages (2008, methodology): “Section 2 defines notation and reviews ideas about permutation inference with instrumental variables from Rosenbaum (1996, 1999, 2002a), Greevy, Silber, Cnaan, and Rosenbaum (2004), and Imbens and Rosenbaum (2005).”
• Local model uncertainty and incomplete‐data bias (with discussion) (2005, unknown): “Rosenbaum (2004) is related to Section 5.2 above and gives a useful review of the author’s pioneering papers on sensitivity analysis, which are also reviewed in Copas and Li (1997).”
• On Sensitivity Value of Pair-Matched Observational Studies (2017, methodology): “Rosenbaum (2004) proposed to select the test statistics to maximize the design sensitivity Γ̃ or equivalently μF in the transformed scale; see also Rosenbaum (2011, 2010b).”
• The Role of Information and Financial Reporting in Corporate Governance and Debt Contracting (2010, background): “In addition, it would be useful for future research to report the sensitivity of reported results to - 88 ‐   the potential omission of relevant variables (e.g., Manski, 1995; Rosenbaum 2002, 2004; Armstrong, Jagolinzer, and Larcker, 2010a).”
• Effect Modification and Design Sensitivity in Observational Studies (2013, methodology): “KEY WORDS: Fisher’s combination of p-values; Power of a sensitivity analysis; Sensitivity analysis; Stephenson’s test; Truncated product of p-values; U-statistic; Wilcoxon test.”