Instrumental Variable Estimation with the R Package ivtools

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Standard

Instrumental Variable Estimation with the R Package ivtools. / Sjolander, Arvid; Martinussen, Torben.

In: Epidemiologic Methods, Vol. 8, No. 1, 20180024, 2019.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Sjolander, A & Martinussen, T 2019, 'Instrumental Variable Estimation with the R Package ivtools', Epidemiologic Methods, vol. 8, no. 1, 20180024. https://doi.org/10.1515/em-2018-0024

APA

Sjolander, A., & Martinussen, T. (2019). Instrumental Variable Estimation with the R Package ivtools. Epidemiologic Methods, 8(1), [20180024]. https://doi.org/10.1515/em-2018-0024

Vancouver

Sjolander A, Martinussen T. Instrumental Variable Estimation with the R Package ivtools. Epidemiologic Methods. 2019;8(1). 20180024. https://doi.org/10.1515/em-2018-0024

Author

Sjolander, Arvid ; Martinussen, Torben. / Instrumental Variable Estimation with the R Package ivtools. In: Epidemiologic Methods. 2019 ; Vol. 8, No. 1.

Bibtex

@article{7ba520a28895485283e7125caa3255ad,
title = "Instrumental Variable Estimation with the R Package ivtools",
abstract = "Instrumental variables is a popular method in epidemiology and related fields, to estimate causal effects in the presence of unmeasured confounding. Traditionally, instrumental variable analyses have been confined to linear models, in which the causal parameter of interest is typically estimated with two-stage least squares. Recently, the methodology has been extended in several directions, including two-stage estimation and so-called G-estimation in nonlinear (e. g. logistic and Cox proportional hazards) models. This paper presents a new R package, ivtools, which implements many of these new instrumental variable methods. We briefly review the theory of two-stage estimation and G-estimation, and illustrate the functionality of the ivtools package by analyzing publicly available data from a cohort study on Vitamin D and mortality.",
keywords = "G-estimation, instrumental variables, mendelian randomization, statistical software, two-stage estimation",
author = "Arvid Sjolander and Torben Martinussen",
year = "2019",
doi = "10.1515/em-2018-0024",
language = "English",
volume = "8",
journal = "Epidemiologic Methods",
issn = "2194-9263",
publisher = "Walterde Gruyter GmbH",
number = "1",

}

RIS

TY - JOUR

T1 - Instrumental Variable Estimation with the R Package ivtools

AU - Sjolander, Arvid

AU - Martinussen, Torben

PY - 2019

Y1 - 2019

N2 - Instrumental variables is a popular method in epidemiology and related fields, to estimate causal effects in the presence of unmeasured confounding. Traditionally, instrumental variable analyses have been confined to linear models, in which the causal parameter of interest is typically estimated with two-stage least squares. Recently, the methodology has been extended in several directions, including two-stage estimation and so-called G-estimation in nonlinear (e. g. logistic and Cox proportional hazards) models. This paper presents a new R package, ivtools, which implements many of these new instrumental variable methods. We briefly review the theory of two-stage estimation and G-estimation, and illustrate the functionality of the ivtools package by analyzing publicly available data from a cohort study on Vitamin D and mortality.

AB - Instrumental variables is a popular method in epidemiology and related fields, to estimate causal effects in the presence of unmeasured confounding. Traditionally, instrumental variable analyses have been confined to linear models, in which the causal parameter of interest is typically estimated with two-stage least squares. Recently, the methodology has been extended in several directions, including two-stage estimation and so-called G-estimation in nonlinear (e. g. logistic and Cox proportional hazards) models. This paper presents a new R package, ivtools, which implements many of these new instrumental variable methods. We briefly review the theory of two-stage estimation and G-estimation, and illustrate the functionality of the ivtools package by analyzing publicly available data from a cohort study on Vitamin D and mortality.

KW - G-estimation

KW - instrumental variables

KW - mendelian randomization

KW - statistical software

KW - two-stage estimation

U2 - 10.1515/em-2018-0024

DO - 10.1515/em-2018-0024

M3 - Journal article

AN - SCOPUS:85074652659

VL - 8

JO - Epidemiologic Methods

JF - Epidemiologic Methods

SN - 2194-9263

IS - 1

M1 - 20180024

ER -

ID: 238854305