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1000 Titel
  • On the logic of collapsibility for causal effect measures
1000 Autor/in
  1. Didelez, Vanessa |
  2. Stensrud, Mats Julius |
1000 Erscheinungsjahr 2021
1000 LeibnizOpen
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2021-02-12
1000 Erschienen in
1000 Quellenangabe
  • 64(2):235-242
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2021
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1002/bimj.202000305 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Liu et al. (2020) discuss the relation between efficacy measures within subgroups and efficacy measures on the population level, which can be obtained by merging the subgroups. They come to the conclusion that neither odds ratios (for binary endpoints) nor hazard ratios (for time-to-event endpoints) are suitable measures of efficacy in this context. This insight is not new, and more general settings have been considered previously (Daniel, Zhang, & Farewell, 2020; Greenland & Pearl, 2011; Greenland, Robins, & Pearl, 1999; Huitfeldt, Stensrud, & Suzuki, 2019; Martinussen & Vansteelandt, 2013; Pang, Kaufman, & Platt, 2013; Sjölander, Dahlqwist, & Zetterqvist, 2016). While we largely agree with their conclusion, we do so for different reasons and would like to point out a number of important subtleties that have perhaps not been appreciated by Liu et al. (2020). These should be carefully understood to avoid any further misleading interpretations. In particular, we want to emphasise, like many before, that confounding and non-collapsibility are separate issues (Didelez et al., 2010; Greenland, 1996; Greenland & Pearl, 2011; Greenland et al., 1999; Pand, Kaufman, & Platt, 2013; Pang et al., 2013; Shrier & Pang, 2015); to cite Greenland (2011): ‘confounding may occur with or without non-collapsibility, and non-collapsibility may occur with or without confounding’. Moreover, in view of patients and investigators preferring contrasts in terms of absolute risks (Murray, Caniglia, Swanson, Hernández-Díaz, & Hernán, 2018), we are sceptical about the emphasis on relative median survival time proposed in Liu et al. (2020).
1000 Sacherschließung
lokal Causal inference
lokal Survival analysis
lokal Collapsibility
lokal Confounding
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0001-8587-7706|https://frl.publisso.de/adhoc/uri/U3RlbnNydWQsIE1hdHMgSnVsaXVz
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  1. On the logic of collapsibility for causal effect measures
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