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The Analysis of Longitudinal Data Using Mixed Model L‐Splines
Author(s) -
Welham Sue J.,
Cullis Brian R.,
Kenward Michael G.,
Thompson Robin
Publication year - 2006
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.1541-0420.2005.00500.x
Subject(s) - mixed model , smoothing spline , spline (mechanical) , mathematics , longitudinal data , smoothing , functional data analysis , context (archaeology) , box spline , computer science , statistics , geography , data mining , spline interpolation , engineering , structural engineering , archaeology , bilinear interpolation
Summary L‐splines are a large family of smoothing splines defined in terms of a linear differential operator. This article develops L‐splines within the context of linear mixed models and uses the resulting mixed model L‐spline to analyze longitudinal data from a grassland experiment. In the spirit of time‐series analysis, a periodic mixed model L‐spline is developed, which partitions data into a smooth periodic component plus smooth long‐term trend.