Using knockoffs for controlled predictive biomarker identification
From MaRDI portal
Publication:6628231
DOI10.1002/SIM.9134zbMATH Open1546.62663MaRDI QIDQ6628231
Konstantinos Sechidis, Matthias Kormaksson, David Ohlssen
Publication date: 29 October 2024
Published in: Statistics in Medicine (Search for Journal in Brave)
false discovery rateknockoff filterheterogeneous treatment effectpredictive biomarker identification
Cites Work
- Title not available (Why is that?)
- Title not available (Why is that?)
- Familywise error rate control via knockoffs
- Controlling the false discovery rate via knockoffs
- Estimation of causal effects with multiple treatments: a review and new ideas
- Recursive partitioning for heterogeneous causal effects
- Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
- Panning for Gold: ‘Model-X’ Knockoffs for High Dimensional Controlled Variable Selection
- A Simple Method for Estimating Interactions Between a Treatment and a Large Number of Covariates
- Deep Knockoffs
- A multiple testing protocol for exploratory data analysis and the local misclassification rate
- Causal Inference for Statistics, Social, and Biomedical Sciences
- Gene hunting with hidden Markov model knockoffs
- Random forests
- Exploratory identification of predictive biomarkers in randomized trials with normal endpoints
- Sequential knockoffs for continuous and categorical predictors: with application to a large psoriatic arthritis clinical trial pool
- Model-based recursive partitioning for subgroup analyses
Related Items (2)
Controlling the false discovery rate by a latent Gaussian copula knockoff procedure ⋮ Modern approaches for evaluating treatment effect heterogeneity from clinical trials and observational data
This page was built for publication: Using knockoffs for controlled predictive biomarker identification
Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6628231)
