Landmarking: Analysis using Landmark Models
Barrott, I, Barrett, J, Keogh, R
, Sweeting, M and Stevens, D
(2022).
Landmarking: Analysis using Landmark Models.
[Dataset].
Comprehensive R Archive Network.
https://cran.r-project.org/package=Landmarking
The landmark approach allows survival predictions to be updated dynamically as new measurements from an individual are recorded. The idea is to set predefined time points, known as "landmark times", and form a model at each landmark time using only the individuals in the risk set. This package allows the longitudinal data to be modelled either using the last observation carried forward or linear mixed effects modelling. There is also the option to model competing risks, either through cause-specific Cox regression or Fine-Gray regression.
Keywords
R package, LandmarkingItem Type | Dataset |
---|---|
Capture method | Other |
Date | 15 February 2022 |
Language(s) of written materials | English |
Creator(s) |
Barrott, I, Barrett, J, Keogh, R |
LSHTM Faculty/Department | Faculty of Epidemiology and Population Health > Dept of Medical Statistics |
Participating Institutions | London School of Hygiene & Tropical Medicine, London, United Kingdom |
Date Deposited | 12 Feb 2020 14:34 |
Last Modified | 15 Aug 2024 14:50 |
Publisher | Comprehensive R Archive Network |
Explore Further
- Comprehensive R Archive Network (Online Data Resource)
- Github (Data)
No files available. Please consult associated links.
- Comprehensive R Archive Network (Online Data Resource)
- Github (Data)
Downloads
ORCID: https://orcid.org/0000-0001-6504-3253