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Nagy, Gabriel; Brunner, Martin; Lüdtke, Oliver; Greiff, Samuel – Journal of Experimental Education, 2017
We present factor extension procedures for confirmatory factor analysis that provide estimates of the relations of common and unique factors with external variables that do not undergo factor analysis. We present identification strategies that build upon restrictions of the pattern of correlations between unique factors and external variables. The…
Descriptors: Factor Analysis, Evaluation Methods, Identification, Correlation
Bryant, Fred B.; Satorra, Albert – Structural Equation Modeling: A Multidisciplinary Journal, 2012
We highlight critical conceptual and statistical issues and how to resolve them in conducting Satorra-Bentler (SB) scaled difference chi-square tests. Concerning the original (Satorra & Bentler, 2001) and new (Satorra & Bentler, 2010) scaled difference tests, a fundamental difference exists in how to compute properly a model's scaling correction…
Descriptors: Statistical Analysis, Structural Equation Models, Goodness of Fit, Least Squares Statistics
Culpepper, Steven Andrew – Applied Psychological Measurement, 2012
Measurement error significantly biases interaction effects and distorts researchers' inferences regarding interactive hypotheses. This article focuses on the single-indicator case and shows how to accurately estimate group slope differences by disattenuating interaction effects with errors-in-variables (EIV) regression. New analytic findings were…
Descriptors: Evidence, Test Length, Interaction, Regression (Statistics)
van Schaik, P.; Martin, S.; Vallance, M. – Journal of Computer Assisted Learning, 2012
In contexts other than immersive virtual environments, theoretical and empirical work has identified flow experience as a major factor in learning and human-computer interaction. Flow is defined as a "holistic sensation that people feel when they act with total involvement". We applied the concept of flow to modeling the experience of…
Descriptors: Structural Equation Models, Interaction, Problem Solving, Psychometrics
Kshirsagar, Anant M.; Radhakrishnan, R. – International Journal of Mathematical Education in Science and Technology, 2009
In a balanced design (i.e. a design in which all cells have the same number of observations), if the effects in the linear model are random and normally distributed, the distribution of the ratio of any sum of squares (s.s.) in the ANOVA to the expected value of its mean square (m.s.) has a [chi][superscript 2]-distribution. In this note, we…
Descriptors: Statistical Analysis, Geometric Concepts, Mathematical Models, Structural Equation Models
Volkwein, J. Fredericks; Yin, Alexander C. – New Directions for Institutional Research, 2010
This chapter summarizes ten selected issues and common problems that arise in most assessment research projects. These include: (1) the uses of grades in assessment; (2) institutional review boards; (3) research design as a compromise; (4) standardized testing; (5) self-reported measures; (6) missing data; (7) weighting data; (8) conditional…
Descriptors: Research Design, Research Methodology, Standardized Tests, Least Squares Statistics
Asparouhov, Tihomir – Structural Equation Modeling, 2005
This article reviews several basic statistical tools needed for modeling data with sampling weights that are implemented in Mplus Version 3. These tools are illustrated in simulation studies for several latent variable models including factor analysis with continuous and categorical indicators, latent class analysis, and growth models. The…
Descriptors: Probability, Structural Equation Models, Sampling, Least Squares Statistics