Outcome-wide longitudinal designs for causal inference: a new template for empirical studies
From MaRDI portal
Publication:2218075
DOI10.1214/19-STS728OpenAlexW3083844724MaRDI QIDQ2218075
Publication date: 12 January 2021
Published in: Statistical Science (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1810.10164
Related Items (1)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Sensitivity Analysis for Unmeasured Confounding in Meta-Analyses
- Control of generalized error rates in multiple testing
- Causal inference through potential outcomes and principal stratification: application to studies with ``censoring due to death
- For objective causal inference, design trumps analysis
- Control of the mean number of false discoveries, Bonferroni and stability of multiple testing
- Applying quantitative bias analysis to epidemiologic data
- Targeted learning in data science. Causal inference for complex longitudinal studies
- A New Criterion for Confounder Selection
- Mediation Analysis with Multiple Mediators
- Identification of Causal Effects Using Instrumental Variables
- What Do Randomized Studies of Housing Mobility Demonstrate?
- Introduction to Meta‐Analysis
- Toward Causal Inference With Interference
- The central role of the propensity score in observational studies for causal effects
- Estimation of the time-dependent accelerated failure time model in the presence of confounding factors
- Inference on Treatment Effects after Selection among High-Dimensional Controls
- A Direct Approach to False Discovery Rates
- Assessing the Sensitivity of Regression Results to Unmeasured Confounders in Observational Studies
- Causal Inference for Statistics, Social, and Biomedical Sciences
- Instrumental variables as bias amplifiers with general outcome and confounding
- Bias attenuation results for nondifferentially mismeasured ordinal and coarsened confounders
- Measurement Error in Nonlinear Models
- An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias
- Misclassification in 2 X 2 Tables
- Observational studies.
- GWAS Catalog
This page was built for publication: Outcome-wide longitudinal designs for causal inference: a new template for empirical studies