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Bianconcini, Silvia – Multivariate Behavioral Research, 2012
In the SEM literature, simplex and latent growth models have always been considered competing approaches for the analysis of longitudinal data, even if they are strongly connected and both of specific importance. General dynamic models, which simultaneously estimate autoregressive structures and latent curves, have been recently proposed in the…
Descriptors: Structural Equation Models, Longitudinal Studies, Academic Achievement, Higher Education
Ryoo, Ji Hoon – Multivariate Behavioral Research, 2011
Model building or model selection with linear mixed models (LMMs) is complicated by the presence of both fixed effects and random effects. The fixed effects structure and random effects structure are codependent, so selection of one influences the other. Most presentations of LMM in psychology and education are based on a multilevel or…
Descriptors: Models, Selection, Data Analysis, Longitudinal Studies
Cham, Heining; West, Stephen G.; Ma, Yue; Aiken, Leona S. – Multivariate Behavioral Research, 2012
A Monte Carlo simulation was conducted to investigate the robustness of 4 latent variable interaction modeling approaches (Constrained Product Indicator [CPI], Generalized Appended Product Indicator [GAPI], Unconstrained Product Indicator [UPI], and Latent Moderated Structural Equations [LMS]) under high degrees of nonnormality of the observed…
Descriptors: Monte Carlo Methods, Computation, Robustness (Statistics), Structural Equation Models
Marsh, Herbert W.; Ludtke, Oliver; Robitzsch, Alexander; Trautwein, Ulrich; Asparouhov, Tihomir; Muthen, Bengt; Nagengast, Benjamin – Multivariate Behavioral Research, 2009
This article is a methodological-substantive synergy. Methodologically, we demonstrate latent-variable contextual models that integrate structural equation models (with multiple indicators) and multilevel models. These models simultaneously control for and unconfound measurement error due to sampling of items at the individual (L1) and group (L2)…
Descriptors: Educational Environment, Context Effect, Models, Structural Equation Models
Beckstead, Jason W. – Multivariate Behavioral Research, 2012
The presence of suppression (and multicollinearity) in multiple regression analysis complicates interpretation of predictor-criterion relationships. The mathematical conditions that produce suppression in regression analysis have received considerable attention in the methodological literature but until now nothing in the way of an analytic…
Descriptors: Multiple Regression Analysis, Predictor Variables, Factor Analysis, Structural Equation Models
van Rosmalen, Joost; Koning, Alex J.; Groenen, Patrick J. F. – Multivariate Behavioral Research, 2009
Multiplicative interaction models, such as Goodman's (1981) RC(M) association models, can be a useful tool for analyzing the content of interaction effects. However, most models for interaction effects are suitable only for data sets with two or three predictor variables. Here, we discuss an optimal scaling model for analyzing the content of…
Descriptors: Class Size, Scaling, Predictor Variables, Models

Marsh, Herbert W.; Hau, Kit-Tai – Multivariate Behavioral Research, 2002
Evaluated multilevel models of growth and change in relation to regression toward the mean artifacts (RTMAs), using simulated data to represent students nested within schools for which there were initial school differences due to selection based on pretest achievement scores. Results demonstrate that multilevel growth models provide no protection…
Descriptors: Academic Achievement, Change, Models, Scores

Marjoribanks, Kevin – Multivariate Behavioral Research, 1976
By using complex multiple regression models to generate regression surfaces, the relationships between academic achievement, creativity, and intelligence are examined. Findings indicate that for certain academic subjects creativity is related to achievement up to a threshold level of intelligence, but after the threshold has been reached…
Descriptors: Academic Achievement, Creativity, Intelligence, Junior High School Students

Tate, Richard L. – Multivariate Behavioral Research, 1981
Analysis of multivariate aptitude-treatment-interaction data is discussed. Analysis procedures are illustrated using data from a science education study to describe the interaction between student reading ability and the time allowed in an individualized instructional approach for multiple achievement and attitudinal outcomes. (Author/RL)
Descriptors: Academic Achievement, Advanced Courses, Aptitude Treatment Interaction, High Schools

Byrne, Barbara M.; Goffin, Richard D. – Multivariate Behavioral Research, 1993
Extent to which findings derived from 4 approaches to multimethod multitrait analyses (MTMM) were consistent in providing estimates of construct validity related to measurement of 4 dimensions of perceived competence across 4 maximally dissimilar rating methods was determined using sample of 158 eleventh graders in Canada. Four MTMM approaches…
Descriptors: Academic Achievement, Construct Validity, English, Estimation (Mathematics)

Grote, Gudela F.; James, Lawrence R. – Multivariate Behavioral Research, 1991
Validity evidence for a new instrument, the Situation-Response Measure of Achievement Motivation for analyzing cross-situational consistency of achievement-related behavior, is presented in a study of 246 college students. Exploratory factor analysis indicates the presence of two factors, striving and apprehensiveness. (SLD)
Descriptors: Academic Achievement, Achievement Need, Behavior Patterns, Coherence

Gustafsson, Jan-Eric; Balke, Gudrun – Multivariate Behavioral Research, 1993
Relations between aptitude variables and school achievement were investigated using a model of ability that permits simultaneous identification of general and specific abilities. Subjects were 866 Swedish students who were given aptitude tests in grade 6; results of that test were compared with course grades collected in grade 9. The usefulness of…
Descriptors: Ability, Ability Identification, Academic Achievement, Aptitude