Literature DB >> 28130316

Response: Formalism or pluralism? A reply to commentaries on 'Causality and causal inference in epidemiology'.

Alex Broadbent1, Jan P Vandenbroucke2, Neil Pearce3.   

Abstract

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Year:  2016        PMID： 28130316      PMCID： PMC5841621          DOI： 10.1093/ije/dyw298

Source DB:  PubMed          Journal:  Int J Epidemiol        ISSN： 0300-5771            Impact factor:   9.685


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  17 in total

Review 1.  Epidemiology as a population science.

Authors:  N Pearce
Journal:  Int J Epidemiol       Date:  1999-10       Impact factor: 7.196

2.  Relation of probability of causation to relative risk and doubling dose: a methodologic error that has become a social problem.

Authors:  S Greenland
Journal:  Am J Public Health       Date:  1999-08       Impact factor: 9.308

3.  Predicting what will happen when we act. What counts for warrant?

Authors:  Nancy Cartwright
Journal:  Prev Med       Date:  2011-08-17       Impact factor: 4.018

Review 4.  Traditional epidemiology, modern epidemiology, and public health.

Authors:  N Pearce
Journal:  Am J Public Health       Date:  1996-05       Impact factor: 9.308

5.  Commentary: Counterfactual causation and streetlamps: what is to be done?

Authors:  James M Robins; Michael B Weissman
Journal:  Int J Epidemiol       Date:  2016-12-01       Impact factor: 7.196

6.  Commentary: On Causes, Causal Inference, and Potential Outcomes.

Authors:  Tyler J VanderWeele
Journal:  Int J Epidemiol       Date:  2016-12-01       Impact factor: 9.685

7.  Epidemiologic measures and policy formulation: lessons from potential outcomes.

Authors:  Sander Greenland
Journal:  Emerg Themes Epidemiol       Date:  2005-05-27

8.  Observational research, randomised trials, and two views of medical science.

Authors:  Jan P Vandenbroucke
Journal:  PLoS Med       Date:  2008-03-11       Impact factor: 11.069

9.  Commentary: The formal approach to quantitative causal inference in epidemiology: misguided or misrepresented?

Authors:  Rhian M Daniel; Bianca L De Stavola; Stijn Vansteelandt
Journal:  Int J Epidemiol       Date:  2016-12-01       Impact factor: 9.685

10.  Authors' Reply to: VanderWeele et al., Chiolero, and Schooling et al.

Authors:  Alex Broadbent; Jan Vandenbroucke; Neil Pearce
Journal:  Int J Epidemiol       Date:  2016-12-01       Impact factor: 7.196
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  9 in total

1.  Epidemiology at a time for unity.

Authors:  Bryan Lau; Priya Duggal; Stephan Ehrhardt
Journal:  Int J Epidemiol       Date:  2018-10-01       Impact factor: 7.196

2.  On Well-defined Hypothetical Interventions in the Potential Outcomes Framework.

Authors:  Tyler J VanderWeele
Journal:  Epidemiology       Date:  2018-07       Impact factor: 4.822

3.  Truer Facts Through Stronger Values: Confronting Science's Sociopolitical Realities.

Authors:  Nadja Eisenberg-Guyot; Jerzy Eisenberg-Guyot
Journal:  New Solut       Date:  2021-11-26

4.  Causal Inference in Environmental Epidemiology: Old and New Approaches.

Authors:  Neil Pearce; Jan P Vandenbroucke; Deborah A Lawlor
Journal:  Epidemiology       Date:  2019-05       Impact factor: 4.822

5.  Emulating Target Trials to Improve Causal Inference From Agent-Based Models.

Authors:  Eleanor J Murray; Brandon D L Marshall; Ashley L Buchanan
Journal:  Am J Epidemiol       Date:  2021-08-01       Impact factor: 4.897

6.  On wagging tales about causal inference.

Authors:  Ashley I Naimi
Journal:  Int J Epidemiol       Date:  2017-08-01       Impact factor: 9.685

7.  Causal inference-so much more than statistics.

Authors:  Neil Pearce; Debbie A Lawlor
Journal:  Int J Epidemiol       Date:  2016-12-01       Impact factor: 7.196

8.  Can Robots Do Epidemiology? Machine Learning, Causal Inference, and Predicting the Outcomes of Public Health Interventions.

Authors:  Alex Broadbent; Thomas Grote
Journal:  Philos Technol       Date:  2022-02-26

9.  Educational note: types of causes.

Authors:  Neil Pearce; Jan P Vandenbroucke
Journal:  Int J Epidemiol       Date:  2020-04-01       Impact factor: 7.196
  9 in total

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