Re: Causality and causal inference in epidemiology: The need for a pluralistic approach

International Journal of Epidemiology

Volumn 45, Issue 6, 2016, Pages 2199-2200

  VanderWeele, Tyler J ^a   Hernán, Miguel A ^a   Tchetgen Tchetgen, Eric J ^a   Robins, James M ^a  

^a HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AMBIGUITY; CAUSALITY; DECISION MAKING; EPIDEMIOLOGICAL DATA; EVIDENCE BASED PRACTICE; HUMAN; LETTER; LOGISTIC REGRESSION ANALYSIS; MICROARRAY ANALYSIS; OUTCOME ASSESSMENT; PRIORITY JOURNAL;

EID: 85017144963     PISSN: 03005771     EISSN: 14643685     Source Type: Journal    
DOI: 10.1093/ije/dyw162     Document Type: Letter

References (8)

1. Vandenbroucke JP, Broadbent A, Pearce N. Causality and causal inference in epidemiology: the need for a pluralistic approach. Int J Epidemiol 2016;45:1776-86.
2. Broadbent A. Causation and prediction in epidemiology: a guide to the 'Methodological Revolution.' Stud Hist Philos Biol Biomed Sci 2015;54:72-80.
3. VanderWeele TJ. Explanation in Causal Inference: Methods for Mediation and Interaction. New York, NY: Oxford University Press, 2015.
4. Robins JM, Greenland S. Comment on 'Causal inference without counterfactuals.' J Am Stat Assoc 2000;95:477-82.
5. Hernán MA, Robins JM. Causal Inference. Boca Raton, FL: Chapman and Hall/CRC, forthcoming.
6. Hernán MA, VanderWeele TJ. Compound treatments and transportability of causal inference. Epidemiology 2011;22:368-77.
7. Tchetgen Tchetgen E. The control outcome calibration approach for causal inference with unobserved confounding. Am J Epidemiol 2014;179:633-40.
8. Robins JM, Hernán MA. In: Fitzmaurice G, DavidianM, Verbeke G, Molenberghs G (eds). Estimation of the causal effects of timevarying exposures, Longitudinal Data Analysis. New York, NY: Chapman and Hall/CRC Press, 2009.