文章基本信息

标题：HIERARCHICAL STRUCTURE OF DENTAL DATA IN THE RANDOM EFFECTS INCLUSION APPROACH
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作者：Tiago Peres da Silva SUGUIURA ; Omar Cléo Neves PEREIRA ; Waenya Fernandez de CARVALHO 等
期刊名称：Revista Brasileira de Biometria
印刷版ISSN：0102-0811
电子版ISSN：1983-0823
出版年度：2018
卷号：36
期号：3
页码：700-714
DOI：10.28951/rbb.v36i3.285
出版社：Universidade Federal de Lavras
摘要：Data sets with complex structures is increasingly common in dental research. As consequences, statistical methods to analyze and interpret these data must be efficient and robust. Hierarchical structures is one of the most common kind of complex structures, and a proper approach is required. The multilevel modeling used to study hierarchical structures is a powerful tool which allows the collected data to be analyzes in several levels. This study has as objective to make a literature review on multilevel linear models and to illustrate a three level model through a matrix procedure, without the use of specific software to estimate the parameters. With this model, we analyzed the vertical gingival retraction when using the substances: Naphazoline Chloridrate, Aluminium Chloride and without any substance. The intraclass correlation coefficient on dental level within patients showed that the hierarchical structure was important to accommodate the dependence within clusters.
关键词：Covariance matrix; Henderson’s equation; mixed models; linear multilevel models; vertical gingival retraction.