斯里兰卡受冲突影响地区学校普通水平成绩的普通教育证书多级建模

D.G.I. Kulawardana, M. Sooriyarachchi
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引用次数: 0

摘要

多层数据结构是由多个分析单元组成的,其中一个在另一个中聚集。多层数据建模的概念已经发展了几年,主要是因为研究者已经意识到忽略这种多层数据结构的缺点。本研究旨在找出斯里兰卡受内战影响省份学校普通教育证书(gce O/L)通过率的影响因素。该研究还扩展到观察学校、地区和省的多层次数据结构,并确定这些水平如何影响gce O/L通过率。以上工作是利用mlwin2.10软件,采用贝叶斯马尔可夫链蒙特卡罗估计方法建立有序分类响应的广义线性多水平模型的高级分析。最后,考虑到部分非比例赔率模型的简单性和准确性,我们选择了部分非比例赔率模型作为本研究中使用的教育数据的最合适模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MULTILEVEL MODELLING OF GENERAL CERTIFICATE OF EDUCATION ORDINARY LEVEL PERFORMANCE OF SCHOOLS IN CONFLICT AFFECTED AREAS IN SRI LANKA
Multilevel data structures are known as consisting of multiple units of analysis, one clustered within the other. The concept of multilevel data modelling has been developed for several years mainly because the researchers have realized the disadvantages of ignoring such multilevel data structures. This study aims to find out factors affecting the General Certificate of Education Ordinary Level (G.C.E. O/L) pass rate at schools located in civil war affected provinces in Sri Lanka. The study also extends to observe the multilevel data structure by schools, districts and provinces, and determine how these levels have an impact on the G.C.E. O/L pass rate. The above has been undertaken by the application of advanced analysis focused on developing Generalized Linear Multilevel Model for ordered categorical response using the Bayesian Markov Chain Monte Carlo estimation method employing MLwiN 2.10 software. Finally, the partial non-proportional odds model was selected as the most appropriate model for the Educational data used in this study based on account of its simplicity and accuracy.    
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