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Peer reviewedCasper, C. A. – Journal of the American Society for Information Science, 1978
This paper explains the theoretical links between the demand for library service and key economic variables, and describes how demand was estimated in one specific experimental context: the demand for library service by institutional users of the Cleveland Health Sciences Library. (Author)
Descriptors: Data Analysis, Economic Research, Income, Information Needs
Peer reviewedMarch, James C.; March, James G. – Administrative Science Quarterly, 1977
This paper considers one system of careers, Wisconsin school superintendents from 1940 through 1972, and examines the extent to which statistical characteristics of that system are consistent with a simple Markov model that assumes both individuals and jobs to be indistinguishable and careers at that level to be essentially random. (Author)
Descriptors: Administrator Characteristics, Career Change, Careers, Elementary Secondary Education
Peer reviewedSclove, Stanley L. – Psychometrika, 1987
A review of model-selection criteria is presented, suggesting their similarities. Some problems treated by hypothesis tests may be more expeditiously treated by the application of model-selection criteria. Multivariate analysis, cluster analysis, and factor analysis are considered. (Author/GDC)
Descriptors: Cluster Analysis, Evaluation Criteria, Factor Analysis, Hypothesis Testing
Peer reviewedYen, Wendy M. – Psychometrika, 1985
An approximate relationship is devised between the unidimensional model used in data analysis and a multidimensional model hypothesized to be generating the item responses. Scale shrinkage is successfully predicted for several sets of simulated data. (Author/LMO)
Descriptors: Difficulty Level, Hypothesis Testing, Item Analysis, Latent Trait Theory
Peer reviewedReichardt, Charles; Gollob, Harry – New Directions for Program Evaluation, 1986
Causal models often omit variables that should be included, use variables that are measured fallibly, and ignore time lags. Such practices can lead to severely biased estimates of effects. The discussion explains these biases and shows how to take them into account. (Author)
Descriptors: Effect Size, Error of Measurement, High Schools, Mathematical Models
Peer reviewedRachman-Moore, Dalia; Wolfe, Richard G. – Journal of Educational Statistics, 1984
A statistical model is proposed that describes the determination of an educational outcome variable as a nonlinear function of explanatory variables defined at different levels of a survey data hierarchy, such as students and classes. The theoretical and practical derivation of the model is discussed, and an example is given. (Author/BW)
Descriptors: Academic Achievement, Educational Assessment, Elementary Secondary Education, Mathematical Models
Peer reviewedHedges, Larry V. – New Directions for Program Evaluation, 1984
The adequacy of traditional effect size measures for research synthesis is challenged. Analogues to analysis of variance and multiple regression analysis for effect sizes are presented. The importance of tests for the consistency of effect sizes in interpreting results, and problems in obtaining well-specified models for meta-analysis are…
Descriptors: Analysis of Variance, Effect Size, Mathematical Models, Meta Analysis
Peer reviewedKatz, Barry M.; McSweeney, Maryellen – Journal of Experimental Education, 1984
This paper developed and illustrated a technique to analyze categorical data when subjects can appear in any number of categories for multigroup designs. Post hoc procedures to be used in conjunction with the presented statistical test are also developed. The technique is a large sample technique whose small sample properties are as yet unknown.…
Descriptors: Data Analysis, Hypothesis Testing, Mathematical Models, Research Methodology
Peer reviewedStavig, Gordon R. – Journal of Experimental Education, 1983
A method is developed for testing a priori multiple regression models. The method allows one to specify in advance as many unstandardized or standardized coefficients as one wants to and allows the remaining slopes to be free to vary. (Author/PN)
Descriptors: Computer Programs, Hypothesis Testing, Mathematical Models, Multiple Regression Analysis
Peer reviewedAndersen, Erling B. – Psychometrika, 1976
A Bradley-Terry type model for paired comparisons is considered which allows for individual parameters and corresponding parameters for the choice-alternatives. Model is applied to data from a Danish investigation of blue collar attitudes towards alternative social gains. Model is compared to one suggested by Schonemann and Wang. (RC)
Descriptors: Comparative Analysis, Data Analysis, Goodness of Fit, Individual Differences
Peer reviewedDick, Daniel T.; Medoff, Marshall H. – Review of Economics and Statistics, 1976
Available from North-Holland Publishing Company, P.O. Box 211, Amsterdam, The Netherlands; $13.50 annually, plus $4.00 postage and handling.
Descriptors: Behavioral Science Research, Educational Background, Employment Level, Employment Practices
Peer reviewedMarin, Alan; Psacharopoulos, George – Review of Economics and Statistics, 1976
Analyzes the relationship between years of schooling and income distribution, based on human capital theory. (Available from North-Holland Publishing Company, P.O. Box 211, Amsterdam, the Netherlands; $13.50 annually, plus $4.00 postage and handling) (JG)
Descriptors: Educational Economics, Elementary Secondary Education, Higher Education, Human Capital
Peer reviewedBloxom, Bruce – Psychometrika, 1972
Special cases of the factor analysis model are developed for four selection situations. Methods are suggested whereby parameters in each case can be estimated using a maximum likelihood procedure recently developed by Joreskog. (Author)
Descriptors: Data Analysis, Factor Analysis, Hypothesis Testing, Mathematical Applications
Peer reviewedMcNamara, James F. – Planning and Changing, 1972
Descriptors: Age, Educational Planning, Enrollment Projections, Enrollment Trends
Peer reviewedTucker, Ledyard R. – Psychometrika, 1972
Descriptors: Factor Analysis, Factor Structure, Mathematical Models, Mathematics


