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Peer reviewedLevin, Martin L. – Simulation and Games, 1970
Descriptors: Adolescents, Mathematical Models, Political Socialization, Simulation
Peer reviewedDickson, E. M. – Bioscience, 1970
Descriptors: Contraception, Demography, Family Planning, Mathematical Models
Schutz, Robert W. – Research Quarterly of the AAHPER, 1970
Descriptors: Athletics, Evaluation, Mathematical Models, Performance Factors
Peer reviewedEastwood, Margaret – Mathematics in School, 1983
Models for developing addition, subtraction, and multiplication with integers are given. (MNS)
Descriptors: Integers, Mathematical Models, Mathematics, Mathematics Instruction
Peer reviewedDunn, Terrence R.; Harshman, Richard A. – Psychometrika, 1982
The kinds of individual differences in perceptions permitted by the weighted euclidean model for multidimensional scaling are more restrictive than those allowed by models developed by Tucker or Carroll. It is shown how problems which occur when using the more general models can be removed. (Author/JKS)
Descriptors: Data Analysis, Individual Differences, Mathematical Models, Multidimensional Scaling
Peer reviewedBuell, Duncan A. – Information Processing and Management, 1981
Discusses several query-processing methods designed to allow the use of relevance weights or thresholds attached to terms and compares them with normal Boolean rules and fuzzy subset theory. Forty-five references are listed. (FM)
Descriptors: Information Retrieval, Mathematical Models, Online Systems, Search Strategies
Peer reviewedFriedman, Sally; Weisberg, Herbert F. – Educational and Psychological Measurement, 1981
The first eigenvalue of a correlation matrix indicates the maximum amount of the variance of the variables which can be accounted for with a linear model by a single underlying factor. The first eigenvalue measures the primary cluster in the matrix, its number of variables and average correlation. (Author/RL)
Descriptors: Correlation, Mathematical Models, Matrices, Predictor Variables
Peer reviewedShapiro, Alexander – Psychometrika, 1982
The extent to which one can reduce the rank of a symmetric matrix by only changing its diagonal entries is discussed. Extension of this work to minimum trace factor analysis is presented. (Author/JKS)
Descriptors: Data Analysis, Factor Analysis, Mathematical Models, Matrices
Peer reviewedWilcox, Rand R. – Educational and Psychological Measurement, 1981
A formal framework is presented for determining which of the distractors of multiple-choice test items has a small probability of being chosen by a typical examinee. The framework is based on a procedure similar to an indifference zone formulation of a ranking and election problem. (Author/BW)
Descriptors: Mathematical Models, Multiple Choice Tests, Probability, Test Items
Peer reviewedKraemer, Helena Chmura – Psychometrika, 1981
Asymptotic distribution theory of Brogden's form of biserial correlation coefficient is derived and large sample estimates of its standard error obtained. Its relative efficiency to the biserial correlation coefficient is examined. Recommendations for choice of estimator of biserial correlation are presented. (Author/JKS)
Descriptors: Correlation, Error of Measurement, Mathematical Models, Nonparametric Statistics
Peer reviewedHedges, Larry V.; Olkin, Ingram – Psychometrika, 1981
Commonality components have been defined as a method of partitioning squared multiple correlations. The asymptotic joint distribution of all possible squared multiple correlations is derived. The asymptotic joint distribution of linear combinations of squared multiple correlations is obtained as a corollary. (Author/JKS)
Descriptors: Correlation, Data Analysis, Mathematical Models, Multiple Regression Analysis
Peer reviewedSnyder, Conrad W., Jr.; Law, Henry G. – Multivariate Behavioral Research, 1979
As psychologists increasingly employ more elaborate and comprehensive data collection schemes, sophisticated analytic techniques will play an ever more important role in understanding behavioral data. This paper outlines one such promising technique, Tucker's three-mode factor analysis, which enables the researcher to explore new taxonomic…
Descriptors: Computer Programs, Factor Analysis, Longitudinal Studies, Mathematical Models
Peer reviewedFinkbeiner, Carl – Psychometrika, 1979
A maximum likelihood method of estimating the parameters of the multiple factor model when data are missing from the sample is presented. A Monte Carlo study compares the method with five heuristic methods of dealing with the problem. The present method shows some advantage in accuracy of estimation. (Author/CTM)
Descriptors: Factor Analysis, Mathematical Models, Maximum Likelihood Statistics, Simulation
Peer reviewedOwston, Ronald D. – Psychometrika, 1979
The method of scoring is used to obtain maximum likelihood estimates of the parameters in White and Clark's (EJ 075 122) learning hierarchy validation model. From the proportion of the population possessing only the superordinate skill in a pair of hierarchical skills, and its variance, the hypothesis of inclusion is tested. (Author/CTM)
Descriptors: Learning, Mathematical Models, Organization, Scoring
Peer reviewedBergan, John R. – Journal of Educational Statistics, 1980
The use of a quasi-equiprobability model in the measurement of observer agreement involving dichotomous coding categories is described. A measure of agreement is presented which gives the probability of agreement under the assumption that observation pairs reflecting disagreement will be equally probable. (Author/JKS)
Descriptors: Judges, Mathematical Models, Observation, Probability


