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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
Hongxi Li; Shuwei Li; Liuquan Sun; Xinyuan Song – Structural Equation Modeling: A Multidisciplinary Journal, 2025
Structural equation models offer a valuable tool for delineating the complicated interrelationships among multiple variables, including observed and latent variables. Over the last few decades, structural equation models have successfully analyzed complete and right-censored survival data, exemplified by wide applications in psychological, social,…
Descriptors: Statistical Analysis, Statistical Studies, Structural Equation Models, Intervals
Van Gasse, Roos; Vanlommel, Kristin; Vanhoof, Jan; Van Petegem, Peter – School Effectiveness and School Improvement, 2017
Research considers collaboration to be a significant factor in terms of how teachers use data to improve their practice. Nevertheless, the effects of teacher collaboration with regard to teachers' individual data use has remained largely underexplored. Moreover, little attention has been paid to the interplay between collaboration and the personal…
Descriptors: Foreign Countries, Teacher Collaboration, Elementary School Teachers, Secondary School Teachers
Elrod, Terry; Haubl, Gerald; Tipps, Steven W. – Psychometrika, 2012
Recent research reflects a growing awareness of the value of using structural equation models to analyze repeated measures data. However, such data, particularly in the presence of covariates, often lead to models that either fit the data poorly, are exceedingly general and hard to interpret, or are specified in a manner that is highly data…
Descriptors: Structural Equation Models, Preferences, Data, Statistical Analysis
Enders, Craig K.; Gottschall, Amanda C. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
Although structural equation modeling software packages use maximum likelihood estimation by default, there are situations where one might prefer to use multiple imputation to handle missing data rather than maximum likelihood estimation (e.g., when incorporating auxiliary variables). The selection of variables is one of the nuances associated…
Descriptors: Structural Equation Models, Statistical Analysis, Data, Factor Analysis
Vanlommel, Kristin; Vanhoof, Jan; Van Petegem, Peter – Educational Studies, 2016
There is a growing expectation that schools should systematically collect and analyse data as a point of departure for decisions. However, research shows that teachers themselves are less convinced that they need to base their decisions on data, as they mainly rely on their intuition and experience. This article examines the extent to which…
Descriptors: Data, Information Utilization, Decision Making, Teacher Motivation
Preacher, Kristopher J.; Zhang, Zhen; Zyphur, Michael J. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
Multilevel modeling (MLM) is a popular way of assessing mediation effects with clustered data. Two important limitations of this approach have been identified in prior research and a theoretical rationale has been provided for why multilevel structural equation modeling (MSEM) should be preferred. However, to date, no empirical evidence of MSEM's…
Descriptors: Data, Structural Equation Models, Statistical Analysis, Computation
Toe, Cleophas Adeodat – ProQuest LLC, 2013
Data security breaches are categorized as loss of information that is entrusted in an organization by its customers, partners, shareholders, and stakeholders. Data breaches are significant risk factors for companies that store, process, and transmit sensitive personal information. Sensitive information is defined as confidential or proprietary…
Descriptors: Information Security, Costs, Corporations, Information Management
Finch, W. Holmes; French, Brian F. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
The purpose of this simulation study was to assess the performance of latent variable models that take into account the complex sampling mechanism that often underlies data used in educational, psychological, and other social science research. Analyses were conducted using the multiple indicator multiple cause (MIMIC) model, which is a flexible…
Descriptors: Causal Models, Computation, Data, Sampling
Residuals and the Residual-Based Statistic for Testing Goodness of Fit of Structural Equation Models
Foldnes, Njal; Foss, Tron; Olsson, Ulf Henning – Journal of Educational and Behavioral Statistics, 2012
The residuals obtained from fitting a structural equation model are crucial ingredients in obtaining chi-square goodness-of-fit statistics for the model. The authors present a didactic discussion of the residuals, obtaining a geometrical interpretation by recognizing the residuals as the result of oblique projections. This sheds light on the…
Descriptors: Structural Equation Models, Goodness of Fit, Geometric Concepts, Algebra
Savalei, Victoria – Structural Equation Modeling: A Multidisciplinary Journal, 2010
Incomplete nonnormal data are common occurrences in applied research. Although these 2 problems are often dealt with separately by methodologists, they often cooccur. Very little has been written about statistics appropriate for evaluating models with such data. This article extends several existing statistics for complete nonnormal data to…
Descriptors: Sample Size, Statistics, Data, Monte Carlo Methods
Yuan, Ke-Hai – Psychometrika, 2009
When data are not missing at random (NMAR), maximum likelihood (ML) procedure will not generate consistent parameter estimates unless the missing data mechanism is correctly modeled. Understanding NMAR mechanism in a data set would allow one to better use the ML methodology. A survey or questionnaire may contain many items; certain items may be…
Descriptors: Structural Equation Models, Effect Size, Data, Maximum Likelihood Statistics

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