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Aguirre-Urreta, Miguel I.; Rönkkö, Mikko; Marakas, George M. – Measurement: Interdisciplinary Research and Perspectives, 2016
One of the central assumptions of the causal-indicator literature is that all causal indicators must be included in the research model and that the exclusion of one or more relevant causal indicators would have severe negative consequences by altering the meaning of the latent variable. In this research we show that the omission of a relevant…
Descriptors: Causal Models, Measurement, Research Problems, Structural Equation Models
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Wang, Jue; Engelhard, George, Jr.; Lu, Zhenqiu – Measurement: Interdisciplinary Research and Perspectives, 2014
The authors of the focus article in this issue have emphasized the continuing confusion among some researchers regarding various indicators used in structural equation models (SEMs). Their major claim is that causal indicators are not inherently unstable, and even if they are unstable they are at least not more unstable than other types of…
Descriptors: Structural Equation Models, Measurement, Statistical Analysis, Causal Models
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Pekrun, Reinhard; Hall, Nathan C.; Goetz, Thomas; Perry, Raymond P. – Journal of Educational Psychology, 2014
A theoretical model linking boredom and academic achievement is proposed. Based on Pekrun's (2006) control-value theory of achievement emotions, the model posits that boredom and achievement reciprocally influence each other over time. Data from a longitudinal study with college students (N = 424) were used to examine the hypothesized effects. The…
Descriptors: Psychological Patterns, Academic Achievement, Causal Models, College Students
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Soenens, Bart; Berzonsky, Michael D.; Papini, Dennis R. – International Journal of Behavioral Development, 2016
Although research suggests an interplay between identity development and self-esteem, most studies focused on the role of identity commitment and measured only level of self-esteem. This study examined longitudinal associations between Berzonsky's (2011) styles of identity exploration and two distinct features of self-esteem: level of self-esteem…
Descriptors: Self Esteem, Individual Development, Longitudinal Studies, Questionnaires
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Coffman, Donna L. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
Mediation is usually assessed by a regression-based or structural equation modeling (SEM) approach that we refer to as the classical approach. This approach relies on the assumption that there are no confounders that influence both the mediator, "M", and the outcome, "Y". This assumption holds if individuals are randomly…
Descriptors: Structural Equation Models, Simulation, Regression (Statistics), Probability
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Ling, Guangming – ETS Research Report Series, 2012
To assess the value of individual students' subscores on the Major Field Test in Business (MFT Business), I examined the test's internal structure with factor analysis and structural equation model methods, and analyzed the subscore reliabilities using the augmented scores method. Analyses of the internal structure suggested that the MFT Business…
Descriptors: Factor Analysis, Construct Validity, Structural Equation Models, Correlation
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Schochet, Peter Z.; Puma, Mike; Deke, John – National Center for Education Evaluation and Regional Assistance, 2014
This report summarizes the complex research literature on quantitative methods for assessing how impacts of educational interventions on instructional practices and student learning differ across students, educators, and schools. It also provides technical guidance about the use and interpretation of these methods. The research topics addressed…
Descriptors: Statistical Analysis, Evaluation Methods, Educational Research, Intervention
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Schochet, Peter Z. – National Center for Education Evaluation and Regional Assistance, 2009
This paper examines the estimation of two-stage clustered RCT designs in education research using the Neyman causal inference framework that underlies experiments. The key distinction between the considered causal models is whether potential treatment and control group outcomes are considered to be fixed for the study population (the…
Descriptors: Control Groups, Causal Models, Statistical Significance, Computation
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Neale, Michael C.; And Others – Multivariate Behavioral Research, 1994
In studies of relatives, conventional multiple regression may not be appropriate because observations are not independent. Obtaining estimates of regression coefficients and correct standard errors from these populations through a structural equation modeling framework is discussed and illustrated with data from twins. (SLD)
Descriptors: Analysis of Covariance, Causal Models, Data Collection, Error of Measurement