Health and Retirement Study
Cross-source consensus on Health and Retirement Study from 1 sources and 5 claims.
1 sources · 5 claims
Benefits
Preparation
Comparisons
Where it comes from
Highlighted claims
- The application analyzed 42,403 HRS participants with complete baseline covariates and at least one BMI measure. — Efficient Bayesian inference for non-linear association structures in joint models: A hierarchical approach via INLA
- Level 3 was strongly preferred over Levels 1 and 2 in the HRS model comparison. — Efficient Bayesian inference for non-linear association structures in joint models: A hierarchical approach via INLA
- BMI was modeled as log(BMI/27), centered at 27 kg/m2. — Efficient Bayesian inference for non-linear association structures in joint models: A hierarchical approach via INLA
- The HRS survival model adjusted for demographic, behavioral, and comorbidity covariates. — Efficient Bayesian inference for non-linear association structures in joint models: A hierarchical approach via INLA
- The HRS application showed that multiple non-linear shared components can be modeled at the same time. — Efficient Bayesian inference for non-linear association structures in joint models: A hierarchical approach via INLA