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The Performance Of Multilevel Structural Equation Modeling (Msem) In Comparison To Multilevel Modeling (Mlm) In Multilevel Mediation Analysis With Non-Normal Data, Thanh Vinh Pham

USF Tampa Graduate Theses and Dissertations

The mediation analysis has been used to test if the effect of one variable on another variable is mediated by the third variable. The mediation analysis answers a question of how a predictor influences an outcome variable. Such information helps to gain understanding of mechanism underlying the variation of the outcome. When the mediation analysis is conducted on hierarchical data, the structure of data needs to be taken into account. Krull and MacKinnon (1999) recommended using Multilevel Modeling (MLM) with nested data and showed that the MLM approach has more power and flexibility over the standard Ordinary Least Squares (OLS) …

Exploring The Test Of Covariate Moderation Effect And The Impact Of Model Misspecification In Multilevel Mimic Models, Chunhua Cao

USF Tampa Graduate Theses and Dissertations

In multilevel MIMIC models, covariates at the between level and at the within level can be modeled simultaneously. Covariates interaction effect occurs when the effect of one covariate on the latent factor varies depending on the level of the other covariate. The two covariates can be both at the between level, both at the within level, and one at the between level and the other one at the within level. And they can create between level covariates interaction, within level covariates interaction, and cross level covariates interaction. Study One purports to examine the performance of multilevel MIMIC models in estimating …

Consequences Of Non-Modeled And Modeled Between Case Variation In The Level-1 Error Structure In Multilevel Models For Single-Case Data: A Monte Carlo Study, Eun Kyeng Baek

USF Tampa Graduate Theses and Dissertations

The Multilevel modeling (MLM) approach has a great flexibility in that can handle various methodological issues that may arise with single-case studies, such as the need to model possible dependency in the errors, linear or nonlinear trends, and count outcomes (e.g.,Van den Noortgate & Onghena, 2003a). By using the MLM framework, researchers can not only model dependency in the errors but also model a variety of level-1error structures.

The effect of misspecification in the level-1 error structure has been well studied for MLM analyses. Generally, it was found that the estimates of the fixed effects were unbiased but the estimates …

A Monte Carlo Study: The Consequences Of The Misspecification Of The Level-1 Error Structure, Merlande Petit-Bois

USF Tampa Graduate Theses and Dissertations

Single-case interventions allow for the repeated measurement of a case or participant across multiple time points, to assess the treatment¡͞s effect on one specific case or participant. The basic interrupted time series design includes two phases: baseline and treatment. Raudenbush and Byrk (2002) demonstrated that a meta-analysis of large group designs can be seen as a special case of multi-level analysis with participants (level-one) nested within studies (level-two). Raw data from a set of single case design studies have a similar structure. Van den Noortgate and Onghena (2003) illustrated the use of a two-level model to analyze data in primary …