Cited by 265Advanced Causal Inference TechniquesStatistical Methods and InferenceGenetic Associations and Epidemiology

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Instrumental Variables Estimation With Some Invalid Instruments and its Application to Mendelian Randomization.

Kang, Hyunseung, Zhang, Anru, Cai, T. Tony, Small, Dylan S.·2016·Journal of the American Statistical Association

DOI 10.1080/01621459.2014.994705

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Abstract

Instrumental variables have been widely used for estimating the causal effect between exposure and outcome. Conventional estimation methods require complete knowledge about all the instruments’ validity; a valid instrument must not have a direct effect on the outcome and not be related to unmeasured confounders. Often, this is impractical as highlighted by Mendelian randomization studies where genetic markers are used as instruments and complete knowledge about instruments’ validity is equivalent to complete knowledge about the involved genes’ functions. In this article, we propose a method for estimation of causal effects when this complete knowledge is absent. It is shown that causal effects are identified and can be estimated as long as less than 50% of instruments are invalid, without knowing which of the instruments are invalid. We also introduce conditions for identification when the 50% threshold is violated. A fast penalized ℓ1 estimation method, called sisVIVE, is introduced for estimating the causal effect without knowing which instruments are valid, with theoretical guarantees on its performance. The proposed method is demonstrated on simulated data and a real Mendelian randomization study concerning the effect of body mass index(BMI) on health-related quality of life (HRQL) index. An R package sisVIVE is available on CRAN. Supplementary materials for this article are available online.

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Authors: Kang, H., Zhang, A., Cai, T. T., & Small, D. S.
ORCID: Kang, Hyunseung
Zhang, Anru
Cai, T. Tony
Small, Dylan S.
Venue: Journal of the American Statistical Association
Publisher: Informa UK Limited
Published: 2016-01-02
Volume: 111
Issue: 513
Pages: 132-144
ISSN: 0162-1459 (ISSN-L)
1537-274X
DOI: 10.1080/01621459.2014.994705
OpenAlex: W1991587639
Cited by: 265
References: 62
Citations by year: 2026: 16 · 2025: 20 · 2024: 28 · 2023: 27 · 2022: 29 · 2021: 18 · 2020: 35 · 2019: 26 · 2018: 26 · 2017: 14 · 2016: 16
FWCI: 19.10
Type: journal article
Language: en
Open access: closed
Locations: Journal of the American Statistical Association (publishedVersion)
ScholarlyCommons (University of Pennsylvania) (submittedVersion)
RePEc: Research Papers in Economics (submittedVersion)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Keywords: instrumental variables, invalid instruments, Mendelian randomization, causal effect estimation, causal identification, genetic instruments, body mass index, health-related quality of life, unmeasured confounding

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Instrumental Variables Estimation With Some Invalid Instruments and its Application to Mendelian Randomization.

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