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Application of Random Coefficient Regression Model to Myopia Data: A Case Study
Author(s) -
Möttonen Jyrki,
Oja Hannu,
Krause Ulf,
Rantakallio Paula
Publication year - 1995
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.4710370603
Subject(s) - statistics , covariate , regression analysis , regression , mathematics , maximum likelihood , random effects model , expectation–maximization algorithm , econometrics , maximization , medicine , mathematical optimization , meta analysis
A one‐year birth cohort from Northern Finland has been followed up since 1966. As a part of this study, we are in this paper concerned with analysing the progression of myopia (nearsightness) up to the age of 20 years. The random coefficient regression model was chosen for the analysis because of the large individual variation in the development of myopia. Maximum likelihood estimates for the parameters in the model were obtained via the expectation maximization (EM) algorithm. It is shown how the estimated model can be used to predict future observations for an individual using the previously recorded refractive error measurements as well as other relevant data on the patient in question.