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Kazuki Hori – ProQuest LLC, 2021
Educational researchers are often interested in phenomena that unfold over time within a person and at the same time, relationships between their characteristics that are stable over time. Since variables in a longitudinal study reflect both within- and between-person effects, researchers need to disaggregate them to understand the phenomenon of…
Descriptors: Time, Structural Equation Models, Monte Carlo Methods, Simulation
Kim, Su-Young; Kim, Jee-Seon – Structural Equation Modeling: A Multidisciplinary Journal, 2012
This article investigates three types of stage-sequential growth mixture models in the structural equation modeling framework for the analysis of multiple-phase longitudinal data. These models can be important tools for situations in which a single-phase growth mixture model produces distorted results and can allow researchers to better understand…
Descriptors: Structural Equation Models, Data Analysis, Research Methodology, Longitudinal Studies
Pena, Deagelia M. – 1994
The multiplicity of variables describing the financial conditions of postsecondary institutions makes it difficult to assess changes in higher education finance from year to year and to find the relationship between these finance variables and average faculty salaries. This study sought to determine if a small number of factors could be derived to…
Descriptors: Budgets, College Faculty, Educational Finance, Factor Analysis