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Peer reviewedWillerding, Margaret F. – School Science and Mathematics, 1972
Descriptors: Algebra, Geometry, History, Mathematical Models
Wells, Peter – Mathematics Teaching, 1971
Descriptors: Algebra, College Mathematics, Geometry, Instruction
Peer reviewedGroen, Guy J. – Psychometrika, 1971
The problem of whether a precise connection exists between the stochastic processes considered in mathematical learning theory and the Guttman simplex is investigated. The approach used is to derive a set of conditions which a probabilistic model must satisfy in order to generate inter-trial correlations with the perfect simplex property.…
Descriptors: Correlation, Learning Theories, Mathematical Models, Probability
Peer reviewedLandrum, William L. – American Educational Research Journal, 1971
See EJ 030 376 and also TM 500 285 in this issue. (CK)
Descriptors: Analysis of Variance, Analytical Criticism, Mathematical Models, Statistical Analysis
Peer reviewedGebhardt, Friedrich – Psychometrika, 1971
Descriptors: Computer Programs, Factor Analysis, Goodness of Fit, Mathematical Models
Peer reviewedWerts, Charles E.; Linn, Robert L. – Educational and Psychological Measurement, 1971
Descriptors: Analysis of Covariance, Analysis of Variance, Mathematical Models, Multiple Regression Analysis
Peer reviewedMielke, Paul T. – Math Teacher, 1970
Descriptors: Arithmetic, Fractions, Geometric Concepts, Mathematical Models
Glenn, John – Mathematics Teaching, 1970
Descriptors: College Mathematics, Economics, Graphs, Mathematical Applications
Arnold, J. C. – J Exp Educ, 1969
Descriptors: Difficulty Level, Guessing (Tests), Mathematical Models, Methods
Vest, Floyd R. – Educ Stud Math, 1969
Descriptors: Addition, Arithmetic, Elementary School Mathematics, Instruction
Peer reviewedRindskopf, David – Psychometrika, 1983
Current computer programs for analyzing linear structural models will apparently handle only two types of constraints: fixed parameter and equal parameters. In this paper, a method for imposing several types of inequality of parameter constraints is described. Several examples are presented. (Author/JKS)
Descriptors: Analysis of Variance, Computer Programs, Data Analysis, Mathematical Models
Peer reviewedRindskopf, David – Psychometrika, 1983
Various models have been proposed for analyzing dichotomous test or questionnaire items which were constructed to reflect an assumed underlying structure (e.g., hierarchical). This paper shows that many such models are special cases of latent class analysis and discusses a currently available computer program to analyze them. (Author/JKS)
Descriptors: Computer Programs, Item Analysis, Mathematical Models, Measurement Techniques
Peer reviewedGrass, Alan L.; Perry, Philippa – Psychometrika, 1983
A procedure for inferring the validity of a selection test as a predictor of some criterion when the available data are limited due to prior selection is described. (Author/JKS)
Descriptors: Mathematical Models, Predictive Measurement, Predictive Validity, Selection
Peer reviewedMellenbergh, Gideon J. – Journal of Educational Statistics, 1982
Strategies for assessing item bias are discussed. Correct response probabilities in latent trait models are compared conditional on latent ability. Probabilities are compared conditional on the observed test score in Scheuneman's method. A method to assess item bias and distinguish between uniform and nonuniform bias is described. (Author/DWH)
Descriptors: Item Analysis, Latent Trait Theory, Mathematical Models, Statistical Studies
Peer reviewedBray, James H.; Maxwell, Scott E. – Review of Educational Research, 1982
The available methods for analyzing and interpreting data with multivariate analysis of variance are reviewed, and guidelines for their use are presented. Causal models that underlie the various methods are presented to facilitate the use and understanding of the methods. (Author/PN)
Descriptors: Analysis of Variance, Discriminant Analysis, Mathematical Models, Multivariate Analysis


