Mixed-Effects Regression Splines to Model Myopia Data

Journal of Biometrics & Biostatistics

article

NordhausenK¹  Oja H¹  PärssinenO³ 

[1] Department of Mathematics and Statistics, University of Turku 20014 Turku;School of Health Sciences, University of Tampere 33014 Tampere;Ophthalmic Department, Central Hospital of Central Finland 40620 Jyväskylä

关键词: Basis function;    B-spline;    Linear mixed model;    Prediction curve;    Principal curve;    Progression;    Truncated polynomial spline;   

DOI  :  10.4172/2155-6180.1000239

来源: Hilaris Publisher

【 摘 要 】

Myopia is a disorder of ocular refraction with varying rates of progression. Although the disorder has a dynamic nature, prospective longitudinal studies with long term follow-ups have been remarkably few. In this paper, we show how mixed-effects regression splines with different choices of basis functions can be used to model myopia progression data in a flexible way. We show how the estimated model may be used to find prediction curves with corresponding confidence and tolerance intervals for a new myopic subject. We discuss alternative choices of the basis functions such as the truncated polynomial spline functions (2 types) and B-spline functions. Principal component functions may be used for an analysis of the variation of the curves in the population. The theory is collected together and presented in a coherent way as well as illustrated with a careful analysis of myopia progression data from a Finnish myopia study.

【 授权许可】

Unknown