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Julia-Kim Walther; Martin Hecht; Benjamin Nagengast; Steffen Zitzmann – Structural Equation Modeling: A Multidisciplinary Journal, 2024
A two-level data set can be structured in either long format (LF) or wide format (WF), and both have corresponding SEM approaches for estimating multilevel models. Intuitively, one might expect these approaches to perform similarly. However, the two data formats yield data matrices with different numbers of columns and rows, and their "cols :…
Descriptors: Data, Monte Carlo Methods, Statistical Distributions, Matrices
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Daniel Seddig – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The latent growth model (LGM) is a popular tool in the social and behavioral sciences to study development processes of continuous and discrete outcome variables. A special case are frequency measurements of behaviors or events, such as doctor visits per month or crimes committed per year. Probability distributions for such outcomes include the…
Descriptors: Growth Models, Statistical Analysis, Structural Equation Models, Crime
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Raykov, Tenko – Structural Equation Modeling: A Multidisciplinary Journal, 2011
This article is concerned with the question of whether the missing data mechanism routinely referred to as missing completely at random (MCAR) is statistically examinable via a test for lack of distributional differences between groups with observed and missing data, and related consequences. A discussion is initially provided, from a formal logic…
Descriptors: Data Analysis, Statistical Analysis, Probability, Structural Equation Models