Multilevel Nonparametric Regression Model with Truncated Linear Spline Estimator on Students' National Examination Scores

Multilevel models can solve problems that arise from data with a hierarchical structure. One application of the use of the multilevel model that has been previously studied in the field of education is the value of the National Examination. The sample size of each district or city is different, causing the Maximum Likelihood estimation method to be appropriate. In addition, there is a tendency that the National Examination scores do not follow a parametric pattern so the truncated spline estimator approach is used. This research examines the application of the multilevel linear spline truncated model. The results obtained are when the number of students is below 76 people, the tendency of the average national exam score to increase, and when the number of students has reached 76 people, the average national exam score can decrease.