کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
415819 | 681240 | 2012 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A Bayesian approach for generalized random coefficient structural equation models for longitudinal data with adjacent time effects
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
This paper proposes a generalized random coefficient structural equation model for analyzing longitudinal data by incorporating the correlated structure due to adjacent time effects and by allowing structural parameters to vary across individuals. The coregionalization for modeling multivariate spatial data is adopted to formulate the correlated structure between adjacent time points. A Bayesian approach coupled with the Gibbs sampler and the Metropolis–Hastings algorithm is developed to obtain the Bayesian estimates of unknown parameters and latent variables simultaneously. A simulation study and a real example related to an emotion study are presented to illustrate the newly developed methodology.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 56, Issue 12, December 2012, Pages 4190–4203
Journal: Computational Statistics & Data Analysis - Volume 56, Issue 12, December 2012, Pages 4190–4203
نویسندگان
Xin-Yuan Song, Nian-Sheng Tang, Sy-Miin Chow,