Modeling repeated measurements data using the multilevel Bayesian network: A case of child morbidity

Abstract

This study reveals that MBN is suitable in modeling repeated measures data to study the relationship between outcomes and estimate rate of change of an outcome over time while quantifying the variability due to higher-level clustering variables. Furthermore, the study highlights the importance of focusing on monitoring children with low WAZ and HAZ scores together with good feeding practices against the frequency of getting flu and diarrhea.