Article

Causal effect heterogeneity estimation using summary statistics

2026-01-14

Abstract excerpt

<title>Abstract</title> <p>Mendelian randomization (MR) has swiftly gained popularity as a tool for causal inference in genetic epidemiology. However, existing MR methods focus exclusively on estimating the average causal effect and cannot quantify its heterogeneity, posing a major methodological limitation and impeding context-dependent causal findings. Here, we introduce MEndelian Randomization for Linear INter...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 8eff751a-e3fc-53e1-b749-0a914a1b4c28
DOI: 10.21203/rs.3.rs-8589460/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Causal effect heterogeneity estimation using summary statisticsDOI 10.21203/rs.3.rs-8589460/v1Read

A Linear Mixed Model with Measurement Error Correction (LMM-MEC): A Method for Summary-data-based Multivariable Mendelian RandomizationSemantic proximity Read

A Linear Mixed Model With Measurement Error Correction (LMM-MEC): A Method for Summary-Data-Based Multivariable Mendelian Randomization.Semantic proximity Read

Benchmarking Mendelian randomization methods for causal inference using genome-wide association study summary statistics.Semantic proximity Read

Mendelian randomization for causal inference accounting for pleiotropy and sample structure using genome-wide summary statistics.Semantic proximity Read

METEOR: a data-adaptive Mendelian randomization method for powerful detection of shared and specific exposures underlying multiple outcomes.Semantic proximity Read

Systematic comparative analysis of Mendelian randomization methods for inferring causal genes of complex phenotypes and the application to psychiatric diseasesSemantic proximity Read

Causal associations between risk factors and common diseases inferred from GWAS summary dataSemantic proximity Read

An augmented Mendelian randomization approach provides causality of brain imaging features on complex traits in a single biobank-scale dataset.Semantic proximity Read

A flexible and unified framework for single- and multi-outcome Mendelian randomization using summary statistics.Semantic proximity Read

Causal associations between risk factors and common diseases inferred from GWAS summary data.Semantic proximity Read

Simultaneous estimation of bi-directional causal effects and heritable confounding from GWAS summary statisticsSemantic proximity Read

Combining Mendelian randomization and network deconvolution for inference of causal networks with GWAS summary data.Semantic proximity Read