Panel Data Analysis of Two Level Mixed Linear Models for Factors Affecting The Health Index in West Java - Awalluddin, Asep Solih; Khumaeroh, Mia Siti; Amalia, H.; Wahyuni, Inge (KUBIK: Jurnal Publikasi Ilmiah Matematika, 2024)
The purpose of this study is to constructÂ a multilevel mixed linear model for panel data by estimating parameters and testing the hypothesis of fit of the model with case studies in determining the prediction of the health index for the marginal and conditional models on the factors that influence the prediction of the health index in West Java for 2016 data. -2021, with time (year) and region (district and city) variables as factors involved in the model. Multilevel mixed linear model is the development of a mixed linear model that can be used to analyze correlated panel data. Parameter estimation uses the Maximum Likelihood (ML) method to estimate fixed effect parameters and Restricted Maximum Likelihood (REML) to estimate covariance parameters. The results obtained by the health index prediction model in West Java, both for the marginal and conditional prediction models and goodness of fit model.