Multilevel Modelling of General Certificate of Education Ordinary Level Performance of Schools in Conflict affected areas in Sri Lanka. - Kulawardene, DGI; Sooriyarachchi, M.R. (EPH, 2017)
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.
Keywords: Bayesian Method, Education, Multilevel data modelling, Ordinal categorical response, Partial non-proportional odds model