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Hill, Richard K., Jr. – 1973
A model for multiple choice test-taking behavior is proposed which is different from those presently used for item sampling theory. A new theory is developed, which includes a new concept to facilitate comprehension of item sampling theory, a "number-known" score distribution. A major advantage of the model is that it accommodates data from…
Descriptors: Item Sampling, Mathematical Models, Norms, Speeches
Dziuban, Charles D.; Harris, Chester W. – 1972
A reanalysis of Shaycroft's matrix of intercorrelations of 10 test variables plus 4 random variables is discussed. Three different procedures were used in the reanalysis: (1) Image Component Analysis, (2) Uniqueness Rescaling Factor Analysis, and (3) Alpha Factor Analysis. The results of these analyses are presented in tables. It is concluded from…
Descriptors: Correlation, Factor Analysis, Mathematical Models, Predictor Variables
PDF pending restorationCOLLIER, RAYMOND O. – 1965
CERTAIN SPECIFIC ASPECTS OF HYPOTHESIS TESTS USED FOR ANALYSIS OF RESULTS IN RANDOMIZED EXPERIMENTS WERE STUDIED--(1) THE DEVELOPMENT OF THE THEORETICAL FACTOR, THAT OF PROVIDING INFORMATION ON STATISTICAL TESTS FOR CERTAIN EXPERIMENTAL DESIGNS AND (2) THE DEVELOPMENT OF THE APPLIED ELEMENT, THAT OF SUPPLYING THE EXPERIMENTER WITH MACHINERY FOR…
Descriptors: Computer Programs, Educational Experiments, Mathematical Models, Research Methodology
Peer reviewedCeurvorst, Robert, W.; Stock, William A. – Multivariate Behavioral Research, 1978
The univariate and multivariate models for the analysis of covariance are compared for the case where an experimental design contains between and within subject factors, one dependent variable, and one observation per subject. (Author/JKS)
Descriptors: Analysis of Covariance, Analysis of Variance, Mathematical Models, Statistical Analysis
Peer reviewedGames, Paul A. – American Educational Research Journal, 1978
Marascuilo's and Levin's use of the term "nesting" to describe a statistical model, and application of the Scheffe tests on restricted sets of contrasts, is opposed. Changing the model during analysis of a complex set of data is both necessary and desirable. (Author/CP)
Descriptors: Data Analysis, Factor Analysis, Hypothesis Testing, Mathematical Models
Peer reviewedWilcox, Rand R. – Journal of Experimental Education, 1985
A new method of measuring item bias based on the latent class model proposed by the author is suggested. A test for item bias is also suggested that is based on standard asymptotic results. (Author/DWH)
Descriptors: Mathematical Models, Measurement Techniques, Statistical Analysis, Test Bias
Peer reviewedSerlin, Ronald C.; Marascuilo, Leonard A. – Journal of Educational Statistics, 1983
Two alternatives to the problems of conducting planned and post hoc comparisons in tests of concordance and discordance for G groups of judges are examined. The two models are illustrated using existing data. (Author/JKS)
Descriptors: Attitude Measures, Comparative Analysis, Interrater Reliability, Mathematical Models
Peer reviewedRindskopf, David – Psychometrika, 1984
Using LISREL, the only types of constraints allowed are fixing parameters at a constant value and constraining parameters to be equal. In this paper, two new concepts ("phantom" and "imaginary" latent variables) are introduced which allow fairly general equality and inequality constraints on factor loadings and structural model…
Descriptors: Computer Software, Factor Analysis, Mathematical Models, Path Analysis
Peer reviewedGoldberger, Arthur S.; Joreskog, Karl G. – Psychometrika, 1972
Descriptors: Algorithms, Factor Analysis, Least Squares Statistics, Mathematical Models
Peer reviewedSirotnik, Ken – Educational and Psychological Measurement, 1972
Investigates implications for finite and known item populations for classical test theory, and the alpha coefficient among items in paper-and-pencil testing. (Author/AG)
Descriptors: Analysis of Variance, Item Sampling, Mathematical Models, Statistical Analysis
Peer reviewedKruskal, J. B. – Psychometrika, 1971
Descriptors: Mathematical Models, Mathematics, Multiple Regression Analysis, Statistical Analysis
Peer reviewedMulaik, Stanley A. – Psychometrika, 1971
Descriptors: Calculus, Factor Analysis, Goodness of Fit, Mathematical Models
Peer reviewedFarr, S. David – American Educational Research Journal, 1971
Descriptors: Data Analysis, Factor Analysis, Mathematical Models, Research Methodology
Peer reviewedHurst, Rex L. – American Educational Research Journal, 1970
Descriptors: Correlation, Mathematical Models, Multiple Regression Analysis, Research Methodology
Peer reviewedMcDonald, Roderick P. – Psychometrika, 1982
Typically, nonlinear models such as those used in the analysis of covariance structures, are not globally identifiable. Investigations of local identifiability must either yield a mapping onto the entire parameter space, or be confined to points of special interest such as the maximum likelihood point. (Author/JKS)
Descriptors: Analysis of Covariance, Mathematical Models, Maximum Likelihood Statistics, Statistical Analysis


