Due to its increasing popularity, hierarchical linear modeling (HLM) has beenused along with structural equation modeling (SEM) to analyze data with nestedstructure. In spite of the extensive research on commonly encountered problems such asviolation of normality and missing data treatment...

Conventional statistical methods assuming data sampled under simple random sampling are inadequate for use on complex survey data with a multilevel structure and non-independent observations. In structural equation modeling (SEM) framework, a researcher can either use the ad-hoc robust sandwich...

This dissertation focuses on issues related to fitting an optimal variance-covariance structure in multilevel linear modeling framework with two Monte Carlo simulation studies. In the first study, the author evaluated the performance of common fit statistics such as Likelihood Ratio Test (LRT),...