Real Effect or Bias? Good Practices for Evaluating the Robustness of Evidence From Comparative Observational Studies Through Quantitative Sensitivity Analysis for Unmeasured Confounding.
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| Title: | Real Effect or Bias? Good Practices for Evaluating the Robustness of Evidence From Comparative Observational Studies Through Quantitative Sensitivity Analysis for Unmeasured Confounding. |
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| Authors: | Faries D; Real-World Access and Analytics, Eli Lilly & Company, Indianapolis, USA., Gao C; Department of Statistics, North Carolina State University, Raleigh, North Carolina, USA., Zhang X; Medical Affairs Biostatistics, CSL Behring, King of Prussia, USA., Hazlett C; Departments of Statistics & Data Science and Political Science, University of California at Los Angeles, Los Angeles, USA., Stamey J; Department of Statistical Science, Baylor University, Waco, USA., Yang S; Department of Statistics, North Carolina State University, Raleigh, North Carolina, USA., Ding P; Department of Statistics, University of California Berkeley, Berkeley, USA., Shan M; Real-World Access and Analytics, Eli Lilly & Company, Indianapolis, USA., Sheffield K; Value, Economics, and Outcomes, Eli Lilly & Company, Indianapolis, USA., Dreyer N; Dreyer Strategies, USA. |
| Source: | Pharmaceutical statistics [Pharm Stat] 2025 Mar-Apr; Vol. 24 (2), pp. e2457. Date of Electronic Publication: 2024 Dec 04. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Wiley Country of Publication: England NLM ID: 101201192 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1539-1612 (Electronic) Linking ISSN: 15391604 NLM ISO Abbreviation: Pharm Stat Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1539-1612 |
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| DOI: | 10.1002/pst.2457 |
