ArticleJournal of the American Statistical Association2019
On the Use of the Lasso for Instrumental Variables Estimation with Some Invalid Instruments.
Article in Journal of the American Statistical Association, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 1 of them a synthesis that pooled it.
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Who cites it
57 citing papers in PubMed, 1 synthesis or guideline pooled it, 155 citations in OpenAlex.
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- A robust and powerful GWAS method for family trios supporting within-family Mendelian randomization analysis.Research square · 2025Article
- Identification and Inference with Invalid Instruments.Annual review of statistics and its application · 2025Article
- Robust Inference for Federated Meta-Learning.Journal of the American Statistical Association · 2025Article
- LASSO-type instrumental variable selection methods with an application to Mendelian randomization.Statistical methods in medical research · 2025Article
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- Best-subset instrumental variable selection method using mixed integer optimization with applications to health-related quality of life and education-wage analyses.Research square · 2024Article
- Bayesian network-based Mendelian randomization for variant prioritization and phenotypic causal inference.Human genetics · 2024Article
- GENIUS-MAWII: for robust Mendelian randomization with many weak invalid instruments.Journal of the Royal Statistical Society. Series B, Statistical methodology · 2024Article
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Corrections and comments
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Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
Abstract
We investigate the behavior of the Lasso for selecting invalid instruments in linear instrumental variables models for estimating causal effects of exposures on outcomes, as proposed recently by Kang et al. Invalid instruments are such that they fail the exclusion restriction and enter the model as explanatory variables. We show that for this setup, the Lasso may not consistently select the invalid instruments if these are relatively strong. We propose a median estimator that is consistent when less than 50% of the instruments are invalid, and its consistency does not depend on the relative strength of the instruments, or their correlation structure. We show that this estimator can be used for adaptive Lasso estimation, with the resulting estimator having oracle properties. The methods are applied to a Mendelian randomization study to estimate the causal effect of body mass index (BMI) on diastolic blood pressure, using data on individuals from the UK Biobank, with 96 single nucleotide polymorphisms as potential instruments for BMI. Supplementary materials for this article are available online.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.