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Instrumental variables estimation under a structural Cox model

(2019) BIOSTATISTICS. 20(1). p.65-79
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Abstract
Instrumental variable (IV) analysis is an increasingly popular tool for inferring the effect of an exposure on an outcome, as witnessed by the growing number of IV applications in epidemiology, for instance. The majority of IV analyses of time-to-event endpoints are, however, dominated by heuristic approaches. More rigorous proposals have either sidestepped the Cox model, or considered it within a restrictive context with dichotomous exposure and instrument, amongst other limitations. The aim of this article is to reconsider IV estimation under a structural Cox model, allowing for arbitrary exposure and instruments. We propose a novel class of estimators and derive their asymptotic properties. The methodology is illustrated using two real data applications, and using simulated data.
Keywords
Causal effect, Cox model, Instrumental variable, Mendelian randomization, Treatment effect on the treated, RANDOMIZED-TRIALS, NONCOMPLIANCE

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Please use this url to cite or link to this publication:

MLA
Martinussen, Torben, Ditte Nørbo Sørensen, and Stijn Vansteelandt. “Instrumental Variables Estimation Under a Structural Cox Model.” BIOSTATISTICS 20.1 (2019): 65–79. Print.
APA
Martinussen, T., Nørbo Sørensen, D., & Vansteelandt, S. (2019). Instrumental variables estimation under a structural Cox model. BIOSTATISTICS, 20(1), 65–79.
Chicago author-date
Martinussen, Torben, Ditte Nørbo Sørensen, and Stijn Vansteelandt. 2019. “Instrumental Variables Estimation Under a Structural Cox Model.” Biostatistics 20 (1): 65–79.
Chicago author-date (all authors)
Martinussen, Torben, Ditte Nørbo Sørensen, and Stijn Vansteelandt. 2019. “Instrumental Variables Estimation Under a Structural Cox Model.” Biostatistics 20 (1): 65–79.
Vancouver
1.
Martinussen T, Nørbo Sørensen D, Vansteelandt S. Instrumental variables estimation under a structural Cox model. BIOSTATISTICS. 2019;20(1):65–79.
IEEE
[1]
T. Martinussen, D. Nørbo Sørensen, and S. Vansteelandt, “Instrumental variables estimation under a structural Cox model,” BIOSTATISTICS, vol. 20, no. 1, pp. 65–79, 2019.
@article{8607771,
  abstract     = {Instrumental variable (IV) analysis is an increasingly popular tool for inferring the effect of an exposure on an outcome, as witnessed by the growing number of IV applications in epidemiology, for instance. The majority of IV analyses of time-to-event endpoints are, however, dominated by heuristic approaches. More rigorous proposals have either sidestepped the Cox model, or considered it within a restrictive context with dichotomous exposure and instrument, amongst other limitations. The aim of this article is to reconsider IV estimation under a structural Cox model, allowing for arbitrary exposure and instruments. We propose a novel class of estimators and derive their asymptotic properties. The methodology is illustrated using two real data applications, and using simulated data.},
  author       = {Martinussen, Torben and Nørbo Sørensen, Ditte and Vansteelandt, Stijn},
  issn         = {1465-4644},
  journal      = {BIOSTATISTICS},
  keywords     = {Causal effect,Cox model,Instrumental variable,Mendelian randomization,Treatment effect on the treated,RANDOMIZED-TRIALS,NONCOMPLIANCE},
  language     = {eng},
  number       = {1},
  pages        = {65--79},
  title        = {Instrumental variables estimation under a structural Cox model},
  url          = {http://dx.doi.org/10.1093/biostatistics/kxx057},
  volume       = {20},
  year         = {2019},
}

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