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@article{J.Gauss4775, author = {Dyan Krismala and Dwi Ispriyanti and Moch. Mukid}, title = {Pemodelan Regresi 2-Level Dengan Metode Iterative Generalized Least Square (IGLS) (Studi Kasus: Tingkat Pendidikan Anak di Kabupaten Semarang)}, journal = {Jurnal Gaussian}, volume = {3}, number = {1}, year = {2014}, keywords = {Hierarchical structure; multistage sampling; 2-level regression}, abstract = {In a research, data was used often hierarchical structure. Hierarchical data is data obtained through multistage sampling from a population with independent variables can be defined within each level and dependent variable can be defined at the lowest level. One analysis that can be used for data with a hierarchical structure is a multilevel regression analysis. Multilevel regression analysis is the most simple regression analysis 2-levels. 2-level regression analysis will be used to construct a regression model the education level of children in Semarang where children (level-1) nested on the distrits (level-2) with the factors that influence. Estimation of parameter in 2-level regression model can use some methods, one of them is Iterative Generalized Least Square (IGLS). From the results of the discussion indicates that the factors which affect the level of education of children in Semarang is the mother’s education, father’ education, and percentage of farm families. The diversity level of the education of children in Semarang caused more variation among children than the variation between districts . }, issn = {2339-2541}, pages = {51--60} doi = {10.14710/j.gauss.3.1.51 - 60}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/4775} }
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