1. Handling Missing Data in the Modeling of Intensive Longitudinal Data Open Access Author: Ji, Linying Title: Handling Missing Data in the Modeling of Intensive Longitudinal Data Graduate Program: Human Development and Family Studies Keywords: intensive longitudinal datamissing datamultiple imputationfull-information maximum likelihood File: Download Masters_thesis_Ji.pdf Committee Members: Sy Miin Chow, Thesis Advisor/Co-AdvisorZita Oravecz, Thesis Advisor/Co-Advisor
2. Missing Data in Multilevel Vector Autoregressive Model: An Evaluation of Missing Data Handling Methods Open Access Author: Ji, Linying Title: Missing Data in Multilevel Vector Autoregressive Model: An Evaluation of Missing Data Handling Methods Graduate Program: Human Development and Family Studies Keywords: Bayesian multilevel vector autoregressive modelmultiple imputationmissing data in longitudinal studiesfull-information maximum likelihood File: Download Dissertation_LJ.pdf Committee Members: Sy-Miin Chow, Dissertation Advisor/Co-AdvisorSy-Miin Chow, Committee Chair/Co-ChairLinda Marie Collins, Committee MemberDouglas Michael Teti, Committee MemberJenae Marie Neiderhiser, Outside MemberDouglas Michael Teti, Program Head/Chair
