| 摘要: | 摘要： Myopia is becoming a significant public health problem, affecting more and more people. Studies indicate that there are two main factors, hereditary and environmental, suspected to have strong impact on myopia. Motivated by the increase in the number of people affected by this problem, this paper focuses primarily on the utilization of mathematical methods to gain further insight into their relationship with myopia. Accordingly, utilizing multidimensional longitudinal myopia data with correlation between both eyes, we develop a Bayesian structural equation model including random effects. With the aid of the MCMC method, it is capable of expressing the correlation between repeated measurements as well as the two‐eye correlation and can be used to explore the relational structure among the variables in the model. We consider four observed factors, including intraocular pressure, anterior chamber depth, lens thickness, and axial length. The results indicate that the genetic effect has much greater influence on myopia than the environmental effects. Copyright © 2011 John Wiley & Sons, Ltd.
其他題名： Statist. Med
出版者： Chichester, UK: John Wiley & Sons, Ltd
出版日期： 2012-01-30
出處： Statistics in medicine, 2012-01, Vol.31 (2), p.188-200
資源來源： Wiley Online Library
版權： Copyright © 2011 John Wiley & Sons, Ltd.
版權： Copyright John Wiley and Sons, Limited Jan 30, 2012
識別號： ISSN: 0277-6715
識別號： ISSN: 1097-0258
識別號： EISSN: 1097-0258
識別號： DOI: 10.1002/sim.4378
識別號： PMID: 21976389
識別號： CODEN: SMEDDA |
