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Time varying mixed effects model with fused lasso regularization.
- Source :
-
Journal of Applied Statistics . May2021, Vol. 48 Issue 8, p1513-1526. 14p. 1 Diagram, 3 Charts, 4 Graphs. - Publication Year :
- 2021
-
Abstract
- The associations between covariates and the outcomes often vary over time, regardless of whether the covariate is time-varying or time-invariant. For example, we hypothesize that the impact of chronic diseases, such as diabetes and heart disease, on people's physical functions differ with aging. However, the age-varying effect would be missed if one models the covariate simply as a time-invariant covariate (yes/no) with a time-constant coefficient. We propose a fused lasso-based time-varying linear mixed effect (FTLME) model and an efficient two-stage parameter estimation algorithm to estimate the longitudinal trajectories of fixed-effect coefficients. Simulation studies are presented to demonstrate the efficacy of the method and its computational efficiency in estimating smooth time-varying effects in high dimensional settings. A real data example on the Health and Retirement Study (HRS) analysis is used to demonstrate the practical usage of our method to infer age-varying impact of chronic disease on older people's physical functions. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 02664763
- Volume :
- 48
- Issue :
- 8
- Database :
- Academic Search Index
- Journal :
- Journal of Applied Statistics
- Publication Type :
- Academic Journal
- Accession number :
- 150447482
- Full Text :
- https://doi.org/10.1080/02664763.2020.1791805