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On instrumental variables estimation of causal odds ratios

Stijn Vansteelandt UGent, Jack Bowden, Manoochehr Babanezhad and Els Goetghebeur UGent (2011) STATISTICAL SCIENCE. 26(3). p.403-422
abstract
Inference for causal effects can benefit from the availability of an instrumental variable (IV) which, by definition, is associated with the given exposure, but not with the outcome of interest other than through a causal exposure effect. Estimation methods for instrumental variables are now well established for continuous outcomes, but much less so for dichotomous outcomes. In this article we review IV estimation of so-called conditional causal odds ratios which express the effect of an arbitrary exposure on a dichotomous outcome conditional on the exposure level, instrumental variable and measured covariates. In addition, we propose IV estimators of so-called marginal causal odds ratios which express the effect of an arbitrary exposure on a dichotomous outcome at the population level, and are therefore of greater public health relevance. We explore interconnections between the different estimators and support the results with extensive simulation studies and three applications.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
Instrumental variable, Marginal effect, Logistic structural mean model., Mendelian randomization, Causal effect, Causal odds ratio, RANDOMIZED CLINICAL-TRIALS, STRUCTURAL MEAN MODELS, MENDELIAN RANDOMIZATION, GENETIC ASSOCIATION, BINARY RESPONSE, NONCOMPLIANCE, INFERENCE, METAANALYSIS, BIAS, IDENTIFICATION
journal title
STATISTICAL SCIENCE
Stat. Sci.
volume
26
issue
3
pages
403 - 422
Web of Science type
Article
Web of Science id
000297043800007
JCR category
STATISTICS & PROBABILITY
JCR impact factor
3.035 (2011)
JCR rank
3/116 (2011)
JCR quartile
1 (2011)
ISSN
0883-4237
DOI
10.1214/11-STS360
project
Bioinformatics: from nucleotids to networks (N2N)
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
1935196
handle
http://hdl.handle.net/1854/LU-1935196
date created
2011-10-25 11:20:43
date last changed
2013-02-27 09:11:29
@article{1935196,
  abstract     = {Inference for causal effects can benefit from the availability of an instrumental variable (IV) which, by definition, is associated with the given exposure, but not with the outcome of interest other than through a causal exposure effect. Estimation methods for instrumental variables are now well established for continuous outcomes, but much less so for dichotomous outcomes. In this article we review IV estimation of so-called conditional causal odds ratios which express the effect of an arbitrary exposure on a dichotomous outcome conditional on the exposure level, instrumental variable and measured covariates. In addition, we propose IV estimators of so-called marginal causal odds ratios which express the effect of an arbitrary exposure on a dichotomous outcome at the population level, and are therefore of greater public health relevance. We explore interconnections between the different estimators and support the results with extensive simulation studies and three applications.},
  author       = {Vansteelandt, Stijn and Bowden, Jack  and Babanezhad, Manoochehr and Goetghebeur, Els},
  issn         = {0883-4237},
  journal      = {STATISTICAL SCIENCE},
  keyword      = {Instrumental variable,Marginal effect,Logistic structural mean model.,Mendelian randomization,Causal effect,Causal odds ratio,RANDOMIZED CLINICAL-TRIALS,STRUCTURAL MEAN MODELS,MENDELIAN RANDOMIZATION,GENETIC ASSOCIATION,BINARY RESPONSE,NONCOMPLIANCE,INFERENCE,METAANALYSIS,BIAS,IDENTIFICATION},
  language     = {eng},
  number       = {3},
  pages        = {403--422},
  title        = {On instrumental variables estimation of causal odds ratios},
  url          = {http://dx.doi.org/10.1214/11-STS360},
  volume       = {26},
  year         = {2011},
}

Chicago
Vansteelandt, Stijn, Jack Bowden, Manoochehr Babanezhad, and Els Goetghebeur. 2011. “On Instrumental Variables Estimation of Causal Odds Ratios.” Statistical Science 26 (3): 403–422.
APA
Vansteelandt, S., Bowden, J., Babanezhad, M., & Goetghebeur, E. (2011). On instrumental variables estimation of causal odds ratios. STATISTICAL SCIENCE, 26(3), 403–422.
Vancouver
1.
Vansteelandt S, Bowden J, Babanezhad M, Goetghebeur E. On instrumental variables estimation of causal odds ratios. STATISTICAL SCIENCE. 2011;26(3):403–22.
MLA
Vansteelandt, Stijn, Jack Bowden, Manoochehr Babanezhad, et al. “On Instrumental Variables Estimation of Causal Odds Ratios.” STATISTICAL SCIENCE 26.3 (2011): 403–422. Print.