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Ashenfelter, Orley – Review of Economics and Statistics, 1978
Available from: the North-Holland Publishing Company, P.O. Box 211, Amsterdam, The Netherlands. (JG)
Descriptors: Data Analysis, Educational Economics, Evaluation Methods, Federal Programs
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Cahan, Sorel; And Others – International Journal of Educational Research, 1987
The estimation and evaluation of the effects of alternative educational or social policies is a major purpose of decision oriented, comparative evaluation studies. This paper reviews the rationale underlying the definition and interpretation of various measures of effect magnitude and examines their relevance to evalution research. (Author)
Descriptors: Control Groups, Decision Making, Educational Assessment, Educational Policy
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Bray, James H.; And Others – Educational and Psychological Measurement, 1984
The purpose of this study was to determise the relative loss in statistical power of traditional methods of analysis when response-shift bias is present. Five methods of analysis (posttest scores only; postminus pretests; postminus retrospective pretest; postcovaried by pretest; postcovaried by retrospective pretest) were compared. (Author/BW)
Descriptors: Analysis of Covariance, Analysis of Variance, Comparative Analysis, Mathematical Models
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Link, Charles; And Others – American Economic Review, 1980
Argues that Blacks have begun to receive monetary benefits from education commensurate with those of Whites and that the gap has narrowed because of the relative upgrading of educational quality for Blacks. Available from American Economic Review, 1313 21st Avenue So., Suite 809, Nashville, TN 37212. (Author/IRT)
Descriptors: Data Analysis, Educational Benefits, Educational Quality, Elementary Secondary Education
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Slovin, Hannah – Mathematics Teaching in the Middle School, 2000
Reports on a research project to use transformation geometry to give students an opportunity to work with proportions using visual models. (YDS)
Descriptors: Evaluation Methods, Geometry, Mathematical Models, Mathematics Curriculum
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Hedges, Larry V. – Journal of Educational Statistics, 1992
The use of statistical methods to combine the results of independent empirical research studies (metanalysis) has a long history, with work mainly divided into tests of the statistical significance of combined results and methods for combining estimates across studies. Methods of metanalysis and their applications are reviewed. (SLD)
Descriptors: Chi Square, Educational Research, Effect Size, Estimation (Mathematics)
Olson, Jeffery E. – 1992
Often, all of the variables in a model are latent, random, or subject to measurement error, or there is not an obvious dependent variable. When any of these conditions exist, an appropriate method for estimating the linear relationships among the variables is Least Principal Components Analysis. Least Principal Components are robust, consistent,…
Descriptors: Error of Measurement, Factor Analysis, Goodness of Fit, Mathematical Models
Hummel, Thomas J. – 1994
Researchers should investigate statistical models that can help counselors decide how to treat individual clients. This research investigated the questions, "Given an effect size (ES) from a counseling outcome study, what is the probability that a client would have a negative response to the treatment, and what is the probability that the client…
Descriptors: Counseling, Counseling Effectiveness, Effect Size, Expectation
Song, Qiang; Chissom, Brad S. – 1993
Since university enrollment forecasting is very important, many different methods and models have been proposed by researchers. Two new methods for enrollment forecasting are introduced: (1) the fuzzy time series model; and (2) the artificial neural networks model. Fuzzy time series has been proposed to deal with forecasting problems within a…
Descriptors: Enrollment Projections, Enrollment Trends, Evaluation Methods, Higher Education
Wise, Lauress L.; McLaughlin, Donald H. – 1980
This guidebook is designed for data analysts who are working with computer data files that contain records with incomplete data. It indicates choices the analyst must make and the criteria for making those choices in regard to the following questions: (1) What resources are available for performing the imputation? (2) How big is the data file? (3)…
Descriptors: Algorithms, Computer Software, Data Analysis, Data Collection
Society for Industrial and Applied Mathematics, Philadelphia, PA. – 1985
The critical role of computers in scientific advancement is described in this panel report. With the growing range and complexity of problems that must be solved and with demands of new generations of computers and computer architecture, the importance of computational mathematics is increasing. Multidisciplinary teams are needed; these are found…
Descriptors: Algorithms, Computer Science, Computer Software, Computers
Doody, Evelyn N. – 1985
The effects of varying degrees of correlation between abilities and of various correlation configurations between item parameters on ability and item parameter estimation using the three parameter logistic model were examined. Ten two-trait configurations and one unidimensional test configuration for 30 item tests were simulated. Each…
Descriptors: Computer Simulation, Estimation (Mathematics), Factor Structure, Item Analysis
Nesselroade, John R.; Baltes, Paul B. – 1977
This manual is intended to improve both the design of longitudinal studies and analysis of the resulting data. Issues related to educational and developmental research have been emphasized in these eight chapters. Topics of particular interest to longitudinal researchers include stochastic models of developmental change, mathematical…
Descriptors: Behavioral Science Research, Data Analysis, Educational Research, Human Development
Murray, James R.; Wiley, David E. – 1970
A basic methodological approach in developmental studies is the collection of longitudinal data. Behavioral data cen take at least two forms, qualitative (or discrete) and quantitative. Both types are fallible. Measurement errors can occur in quantitative data and measures of these are based on error variance. Qualitative or discrete data can…
Descriptors: Behavioral Sciences, Data Analysis, Evaluation Methods, Feedback
Levin, Joel R.; Marascuilo, Leonard A. – 1971
Marascuilo and Levin's (1970) notion of Type IV errors is extended, with respect to the interpretation of interactions in analysis of variance (ANOVA) designs. To help clarity what an interaction is and what it is not, in terms of the ANOVA model, the following points are made: (i) interactions should be thought of as linear contrasts involving…
Descriptors: Analysis of Variance, Behavioral Science Research, Evaluation Methods, Hypothesis Testing
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