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What Works Clearinghouse Rating
Design and Analysis Problems Associated with Qualitative Data in Educational Research. Final Report.
Fienberg, Stephen E.; Larntz, Kinley – 1979
This research project addresses a series of methodological and theoretical statistical problems in the analysis of categorical data using loglinear and logistic response models, which grow directly out of problems in the study of the American educational system, and in basic educational research. The project focuses on the adaptation and…
Descriptors: Data Analysis, Educational Research, Mathematical Models, Research Problems
Peer reviewedPlewis, Ian – Journal of Educational Statistics, 1981
Simple Markov models are fitted to a small sample of longitudinal categorical data of teachers' ratings of children's classroom behavior. Although the data consist only of observations at five occasions, it was possible, after dividing the data into two groups, to fit plausible models in continuous time. (Author/BW)
Descriptors: Longitudinal Studies, Mathematical Models, Research Problems, Statistical Analysis
Peer reviewedSachar, Jane – Journal of Experimental Education, 1980
The partial correlation coefficient is derived analytically under exemplary factor patterns. In these patterns, variables are described as an additive composition of a set of orthogonal factors, including general, common, and specific factors. Viewed in this framework, it is evident that the partial correlation may yield spurious results.…
Descriptors: Correlation, Factor Analysis, Factor Structure, Mathematical Models
Sockloff, Alan L. – 1974
An equation was derived to determine the relationship between the pooled within-subgroup r (correlation coefficient) and the r obtained from the total group data. It was, thus, possible to assess the amount of distortion introduced by pooling heterogeneous subgroups. As a basis for deciding whether to pool two subgroups in order to calculate a…
Descriptors: Analysis of Variance, Correlation, Hypothesis Testing, Mathematical Models
Peer reviewedWilliams, John D. – Multiple Linear Regression Viewpoints, 1977
The problems of two way analysis of variance designs with unequal and disproportionate cell sizes are discussed. A variety of solutions are discussed and a new solution is presented. (JKS)
Descriptors: Analysis of Variance, Hypothesis Testing, Mathematical Models, Matrices
Pravalpruk, Kowit; Porter, Andrew C. – 1974
When random assignment has been accomplished and an analysis of covariance (ANCOVA) is being used to correct for initial differences among treatment groups, use of unreliable covariables not only decreases the power of ANCOVA, but also causes ANCOVA to test biased treatment effects. Several correction procedures have been suggested for the single…
Descriptors: Analysis of Covariance, Mathematical Models, Research Problems, Statistical Analysis
Timm, Neil H. – 1977
Several procedures proposed in the literature for the analysis of growth curves are reviewed. Particular attention is given to the current issues in this area to guide practitioners in the selection of the most appropriate methodology. (Author)
Descriptors: Analysis of Covariance, Analysis of Variance, Hypothesis Testing, 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 reviewedHopkins, Kenneth D. – American Educational Research Journal, 1982
The recommendation to use group means when there may be nonindependence among observational units is unduly restrictive. When random factors are properly identified and included in the analysis, the results are identical in balanced analysis of variance designs, irrespective of whether group means or individual observations are employed.…
Descriptors: Analysis of Variance, Data Analysis, Hypothesis Testing, Mathematical Models
Peer reviewedWilson, Thomas P. – Sociological Methods and Research, 1979
A recent recommendation by Holt (EJ 200 576) that coefficients resulting from estimating log-linear and similar models should not be interpreted is argued to be based on lack of clarity about the substantive and theoretical importance of the choice between dummy and effect coding for categorical variables. (Author/GDC)
Descriptors: Expectancy Tables, Goodness of Fit, Mathematical Models, Probability
Wilcox, Rand R. – 1979
Three separate papers are included in this report. The first describes a two-stage procedure for choosing from among several instructional programs the one which maximizes the probability of passing the test. The second gives the exact sample sizes required to determine whether a squared multiple correlation coefficient is above or below a known…
Descriptors: Bayesian Statistics, Correlation, Hypothesis Testing, Mathematical Models
Lai, Morris K. – 1974
When analysis of variance is used, statistically significant differences may or may not be of practical significance to educators. A large part of the problem is due to the fact that a "zero difference" null hypothesis can always be rejected statistically if the sample size is large enough. If, however, a method based on the noncentral F…
Descriptors: Analysis of Variance, Data Analysis, Hypothesis Testing, Mathematical Models
Peer reviewedBlair, R. Clifford; Higgings, J. J. – American Educational Research Journal, 1978
Kaufman and Sweet's article on the regression analysis of unbalanced factorial designs (EJ 111 767) is reviewed. A number of errors are noted, and relevant literature is cited. (GDC)
Descriptors: Least Squares Statistics, Mathematical Models, Multiple Regression Analysis, Research Design
Peer reviewedMaxwell, Scott E.; Howard, George S. – Educational and Psychological Measurement, 1981
This paper delineates conditions under which the use of change scores will not produce misleading results, and may perhaps be preferable to other methods of analysis. The validity of change scores in randomized pretest-posttest designs is discussed along with situations where analysis of change scores should be used. (Author/GK)
Descriptors: Analysis of Covariance, Analysis of Variance, Mathematical Models, Pretests Posttests
Hedges, Larry V. – 1982
Meta-analysis has become an important supplement to traditional methods of research reviewing, although many problems must be addressed by the reviewer who carries out a meta-analysis. These problems include identifying and obtaining appropriate studies, extracting estimates of effect size from the studies, coding or classifying studies, analyzing…
Descriptors: Analysis of Variance, Correlation, Error of Measurement, Mathematical Models


