A Multiple Imputation Approach for the Evaluation of Surrogate Markers in the Principal Stratification Causal Inference Framework
From MaRDI portal
Publication:4984852
DOI10.1007/978-1-4614-8981-8_18zbMath1461.62190OpenAlexW2207864437MaRDI QIDQ4984852
Xiaoming Li, I. S. F. Chan, Xiaopeng Miao, Peter B. Gilbert
Publication date: 20 April 2021
Published in: Risk Assessment and Evaluation of Predictions (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/978-1-4614-8981-8_18
Related Items (1)
Cites Work
- Unnamed Item
- Simple relations between principal stratification and direct and indirect effects
- Assessing surrogate endpoints in vaccine trials with case-cohort sampling and the Cox model
- Comparing Biomarkers as Principal Surrogate Endpoints
- Multiple Imputation Methods for Multivariate One-Sided Tests with Missing Data
- Statistical Identifiability and the Surrogate Endpoint Problem, with Application to Vaccine Trials
- Multiple Imputation Approaches for the Analysis of Dichotomized Responses in Longitudinal Studies with Missing Data
- Principal Stratification in Causal Inference
- The Robust Inference for the Cox Proportional Hazards Model
- Evaluating Candidate Principal Surrogate Endpoints
- A Bayesian Approach to Surrogacy Assessment Using Principal Stratification in Clinical Trials
- Related Causal Frameworks for Surrogate Outcomes
- A case-cohort design for epidemiologic cohort studies and disease prevention trials
- Direct and Indirect Causal Effects via Potential Outcomes*
- Augmented Designs to Assess Immune Response in Vaccine Trials
This page was built for publication: A Multiple Imputation Approach for the Evaluation of Surrogate Markers in the Principal Stratification Causal Inference Framework