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Hidayat, Riyan; Idris, Wan Izani Wan; Qudratuddarsi, Hilman; Rahman, Muhamad Nazri Abdul – EURASIA Journal of Mathematics, Science and Technology Education, 2021
This work sets out to examine the validity and reliability of the Mathematical Modeling Attitude Scale (MMAS), a instrument measuring teachers' attitude towards mathematical modeling. A cross-sectional survey research was utilised to describe the validity and reliability of the MMAS. The population of the present study focused on Malaysian…
Descriptors: Factor Analysis, Student Motivation, Student Interests, Constructivism (Learning)
Williams, Thomas O., Jr.; Fall, Anna-Maria; Eaves, Ronald C.; Darch, Craig; Woods-Groves, Suzanne – Assessment for Effective Intervention, 2007
The factor structure of the "KeyMath--Revised Normative Update" (KMR-NU) "Form A" was analyzed using data from a sample of 130 students. The KMR-NU is composed of 13 subtests that are purported to measure three important aspects of math ability: Basic Concepts, Operations, and Applications. A confirmatory factor analysis…
Descriptors: Mathematical Models, Goodness of Fit, Academic Ability, Mathematics

van Prooijen, Jan-Willem; van der Kloot, Willem A. – Educational and Psychological Measurement, 2001
Assessed the extent to which results in exploratory factor analysis (EFA) studies can be replicated by confirmatory factor analysis in the same sample. Used 10 factor structures drawn from the literature. Results show that confirmatory factor models in which all low EFA pattern coefficients were fixed to zero fitted especially poorly. (SLD)
Descriptors: Factor Structure, Mathematical Models

Mulaik, Stanley A.; Quartetti, Douglas A. – Structural Equation Modeling, 1997
The Schmid-Leiman (J. Schmid and J. M. Leiman, 1957) decomposition of a hierarchical factor model converts the model to a constrained case of a bifactor model with orthogonal common factors that is equivalent to the hierarchical model. This article discusses the equivalence of the hierarchical and bifactor models. (Author/SLD)
Descriptors: Factor Analysis, Factor Structure, Mathematical Models

Maraun, Michael D.; Rossi, Natasha T. – Applied Psychological Measurement, 2001
Demonstrated that the extra-factor phenomenon (the two-dimensional solution produced when linear factor analysis is applied to a set of unfoldable items) arises because the metric unidimensional unfolding model is equivalent to the unidimensional quadratic factor model and the unidimensional quadratic factor model is not distinguishable from the…
Descriptors: Factor Analysis, Factor Structure, Mathematical Models
Donders, Jacobus – Assessment, 2008
The purpose of this study is to determine the latent structure of the California Verbal Learning Test-Second Edition (CVLT-II; Delis, Kramer, Kaplan, & Ober, 2000) at three different age levels, using the standardization sample. Maximum likelihood confirmatory factor analyses are performed to test four competing hypothetical models for fit and…
Descriptors: Attention Span, Verbal Learning, Factor Structure, Factor Analysis
Trendafilov, Nickolay T. – 1992
In the technique developed by K. G. Joreskog to solve the problem for oblique rotation to a specified simple structure, the basic concept is that the simple structure solution itself is determined only by the zero coefficients of the reference-structure matrix and not by the coefficients of non-zero magnitude. Following this, prior information…
Descriptors: Equations (Mathematics), Factor Structure, Mathematical Models, Psychological Testing

Boruch, Robert F.; And Others – Educational and Psychological Measurement, 1970
Descriptors: Analysis of Variance, Factor Analysis, Factor Structure, Mathematical Models

Maraun, Michael D.; And Others – Multivariate Behavioral Research, 1996
The issue of indeterminacy in factor analysis and the debate between the proposed alternative solution and posterior moment position are explored in an article and 14 commentaries and rebuttals in two rounds. Implications for applied work involving factor analysis are discussed. (SLD)
Descriptors: Factor Analysis, Factor Structure, Mathematical Models, Metaphors
Hester, Yvette – 1996
Data reduction techniques seek to combine variables that account for patterns of variation in observed dependent variables in such a way that a simpler model is available for analysis. Factor analysis is a data reduction technique that attempts to model or explain a set of variables in terms of their associations. To understand why this technique…
Descriptors: Factor Analysis, Factor Structure, Heuristics, Mathematical Models

Martin, James K.; McDonald, Roderick P. – Psychometrika, 1975
A Bayesian procedure is given for estimation in unrestricted common factor analysis. A choice of the form of the prior distribution is justified. The procedure achieves its objective of avoiding inadmissible estimates of unique variances, and is reasonably insensitive to certain variations in the shape of the prior distribution. (Author/BJG)
Descriptors: Bayesian Statistics, Factor Analysis, Factor Structure, Mathematical Models
Lord, Frederic M.; Wingersky, Marilyn S. – 1971
Explicit formulas are derived for the asymptotic sampling variances and covariances of the maximum likelihood estimators for factor-analysis parameters in the special case where there is just one common factor. The effect of the number of variables on these variances and covariances is indicated. A formula is given showing to what extent the usual…
Descriptors: Factor Analysis, Factor Structure, Mathematical Models, Mathematics

Harper, Dean – Psychometrika, 1972
A procedure is outlined showing how the axiom of local independence for latent structure models can be weakened. (CK)
Descriptors: Algorithms, Factor Analysis, Factor Structure, Mathematical Applications

Gati, Itamar – Educational and Psychological Measurement, 1981
This paper examines the properties of the Item Efficiency Index proposed by Neill and Jackson (1976; EJ 137 077) for minimum redundancy item analysis. (Author/BW)
Descriptors: Correlation, Factor Structure, Item Analysis, Mathematical Models

Hill, P. W.; McGaw, B. – American Educational Research Journal, 1981
In an attempt to resolve conflicting conclusions arising from an investigation of the validity of the claimed psychological properties of Bloom's taxonomy, the LISREL method was applied to the data of Kropp and Stoker. The simplex assumption was supported when the knowledge category is deleted from the taxonomy. (Author/RL)
Descriptors: Classification, Factor Structure, Goodness of Fit, Hypothesis Testing