Abstract:
When data with correlated responses are available, joint models may provide interesting and
improved results than modeling the responses separately. Such models between those
responses can be developed and their applicability in various fields is noteworthy. Though joint
mixed models and joint population averaged models are popular and common in statistical
literature, Joint Marginalized Multilevel Models (JMMM) is still a developing area. Thus, the
main objective of the study is to model survival and count data jointly, utilizing MMM and
applying it to data related to Distance Education in Sri Lanka. The data obtained for this study
represents records of students who have registered for undergraduate study program in
Management at a leading higher education institute in Sri Lanka through Open and Distance
Learning (ODL), which conducts the program in all the regional/ study centers across the
country. As the students are clustered in different regional/ study centers, the clustering effect
is also present in the dataset. In this study, completion time of study programs by the students
is considered as a survival response and the number of first time passes by students, which
represents student performance, is considered as the count variable. The findings suggest that
the time to completion of the study program and gender have a significant impact on
completion of the study program and student performance in the said context.
