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Hullett, Craig R.; Levine, Timothy R. – Communication Monographs, 2003
Notes that because estimates of effect sizes are often either misreported or not reported at all, meta-analysts must use conversion formulas that allow estimates of effect sizes from information available. Focuses on formulas that convert "F" in ANOVA, a statistical test, to eta-squared, "d," or the correlation equivalent. Demonstrates that the…
Descriptors: Effect Size, Estimation (Mathematics), Higher Education, Mathematical Models

Bechger, Timo M.; Verstralen, Huub H. F. M.; Verhelst, Norma D. – Psychometrika, 2002
Discusses the Linear Logistic Test Model (LLTM) and demonstrates that there are many equivalent ways to specify a model. Analyzed a real data set (300 responses to 5 analogies) using a Lagrange multiplier test for the specification of the model, and demonstrated that there may be many ways to change the specification of an LLTM and achieve the…
Descriptors: Equations (Mathematics), Goodness of Fit, Item Response Theory, Mathematical Models

Boaler, Jo – Teaching Mathematics and Its Applications, 2001
Demonstrates the importance of expanding notions of learning beyond knowledge to the practices in mathematics classrooms. Considers a three-year study of students who learned through mathematical modeling. Shows that a modeling approach encouraged the development of a range of important practices in addition to knowledge that were useful in real…
Descriptors: Learning Theories, Longitudinal Studies, Mathematical Models, Mathematics Education

Watson, Jane M.; Moritz, Jonathan B. – Educational Studies in Mathematics, 2001
Proposes a developmental model involving four response levels concerning how students arrange pictures to represent data in a pictograph, how they interpret these pictographs, and how they make predictions based on these pictographs. The model is exemplified by responses from three related interview-based studies. Discusses educational…
Descriptors: Elementary Secondary Education, Mathematical Models, Mathematics Education, Thinking Skills

Mayer-Foulkes, David – Economics of Education Review, 2002
Develops an inter-temporal optimization model linking academic achievement reputation, and the pool of student quality available to an institution. Describes empirical study of student-quality dynamics and its relation to the model. Finds that SAT levels of attracted students follow a convergent process as predicted, with graduation rates,…
Descriptors: College Choice, Enrollment Influences, Graduation, Higher Education

Bart, William M.; Williams-Morris, Ruth – Applied Measurement in Education, 1990
Refined item digraph analysis (RIDA) is a way of studying diagnostic and prescriptive testing. It permits assessment of a test item's diagnostic value by examining the extent to which the item has properties of ideal items. RIDA is illustrated with the Orange Juice Test, which assesses the proportionality concept. (TJH)
Descriptors: Diagnostic Tests, Evaluation Methods, Item Analysis, Mathematical Models

McClelland, James L. – Cognitive Psychology, 1991
Mathematical analysis and computer simulation methods are used to show that interactive models of context effects can exhibit classical context effects if there is variability in the input to the network or the network itself. Interactive models represent hypotheses about information-processing dynamics leading to the global asymptotic behaviors…
Descriptors: Computer Simulation, Context Effect, Equations (Mathematics), Graphs

Nosofsky, Robert M. – Cognitive Psychology, 1991
This paper proposes that patterns of proximity data that have been characterized in terms of asymmetric similarity may be alternatively characterized in terms of differential bias. An additive similarity and bias model is reviewed, and it is proposed that biases can be stimulus based as well as response based. (SLD)
Descriptors: Bias, Classification, Equations (Mathematics), Mathematical Models

Holmes, D. J. – Psychometrika, 1990
A theoretical framework is developed in which the effects of some common forms of violation of assumptions of linearity of regression and homoscedasticity can be investigated. Simple expressions are derived for the restricted and corrected correlations in terms of the target (unrestricted) correlation in these situations. (SLD)
Descriptors: Correlation, Equations (Mathematics), Mathematical Models, Regression (Statistics)

Nie, Jianyun – Information Processing and Management, 1989
Argues that most currently used information retrieval models are unsuitable to describe recent techniques such as semantic based retrieval. A more general model is presented in which the basis for information retrieval is viewed as logical implication and the estimation of the correspondence between queries and documents is described in terms of…
Descriptors: Evaluation Criteria, Information Retrieval, Logic, Mathematical Models

Adams, Arthur J.; Shiffler, Ronald E. – Educational and Psychological Measurement, 1989
New methods of analysis--equations and graphs for iso-r(sup 2) contours--were introduced and used to illustrate location effects for pooled data sets. The "r(sup 2)" is the coefficient of determination. Results are used to highlight imprecise statements in the literature about the behavior of the correlation coefficient for pooled data…
Descriptors: Correlation, Equations (Mathematics), Graphs, Mathematical Models

Laird, Nan M.; Louis, Thomas A. – Journal of Educational Statistics, 1989
Based on the Gaussian model, methods for using measurements that depend on the true attribute to compute rankings are proposed and compared. Measurements based on an empirical Bayes model produce estimates that differ from ranking observed data. Ranking methods are illustrated with school achievement data. (TJH)
Descriptors: Bayesian Statistics, Class Rank, Mathematical Formulas, Mathematical Models

Tanaka, Yutaka; Odaka, Yoshimasa – Psychometrika, 1989
A method is proposed for detecting influential observations in iterative principal factor analysis. Theoretical influence functions are derived for two components of the common variance decomposition. The major mathematical tool is the influence function derived by Tanaka (1988). (SLD)
Descriptors: Equations (Mathematics), Factor Analysis, Mathematical Models, Research Methodology

Woodruff, David J. – Applied Psychological Measurement, 1989
Linear equating methods for the common-item non-equivalent populations design were compared when true-score correlation between the test and anchor was less than unity. Scores from two groups of approximately 300 examinees illustrated three methods: (1) the Tucker equating method; (2) the Angoff-Levine method; and (3) the Congeneric-Levine method.…
Descriptors: Comparative Analysis, Equated Scores, Mathematical Models, Research Design

Umesh, U. N.; And Others – Educational and Psychological Measurement, 1989
An approach is provided for calculating maximum values of the Kappa statistic of J. Cohen (1960) as a function of observed agreement proportions between evaluators. Separate calculations are required for different matrix sizes and observed agreement levels. (SLD)
Descriptors: Equations (Mathematics), Evaluators, Heuristics, Interrater Reliability