Dynamic Pseudo‐Observations: A Robust Approach to Dynamic Prediction in Competing Risks
From MaRDI portal
Publication:5408028
DOI10.1111/biom.12061zbMath1288.62151OpenAlexW1933685677WikidataQ43513708 ScholiaQ43513708MaRDI QIDQ5408028
Mioara Alina Nicolaie, T. M. de Witte, Hein Putter, Hans C. van Houwelingen
Publication date: 8 April 2014
Published in: Biometrics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1111/biom.12061
Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12) Estimation in survival analysis and censored data (62N02)
Related Items
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Dynamic predicting by landmarking as an alternative for multi-state modeling: an application to acute lymphoid leukemia data
- On pseudo-values for regression analysis in competing risks models
- Competing Risks and Time-Dependent Covariates
- Predicting cumulative incidence probability by direct binomial regression
- Generalised linear models for correlated pseudo-observations, with applications to multi-state models
- A Proportional Hazards Model for the Subdistribution of a Competing Risk
- Prediction Using Partly Conditional Time‐Varying Coefficients Regression Models
- Incorporating short‐term outcome information to predict long‐term survival with discrete markers
- Regression Analysis for Multistate Models Based on a Pseudo‐value Approach, with Applications to Bone Marrow Transplantation Studies
- Dynamic Prediction by Landmarking in Event History Analysis
- Directly parameterized regression conditioning on being alive: analysis of longitudinal data truncated by deaths
- Regression Modeling of Competing Risks Data Based on Pseudovalues of the Cumulative Incidence Function
