Loglinear Model Formation using Hierachial Backward Method - Sihotang, Siti Fatimah; Zuhri, (Journal of Research in Mathematics Trends and Technology, 2020)
The loglinear model is a special case of a general linear model for poisson distributed data. The loglinear model is also a number of models in statistics that are used to determine dependencies between several variables on a categorical scale. The number of variables discussed in this study were three variables. After the variables are investigated, the formation of the loglinear model becomes important because not all the model interaction factors that exist in the complete model become significant in the resulting model. The formation of the loglinear model in this study uses the Backward Hierarchical method. This research makes loglinear modeling to get the model using the Hierarchical Backward method to choose a good method in making models with existing examples. From the challenging examples that have been done, it is known that the Hierarchical Reverse method can model the third iteration or scroll. Then, also use better assessment methods about faster workmanship and computer-sponsored assessments that are used more efficiently through compatibility testing for each model made