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Joe, George W.; Mendoza, Jorge L. – Journal of Educational Statistics, 1989
A response to comments on internal correlation for statistical analysis, as proposed by the present authors (1989), is provided. Focus is on issues raised by W. W. Rozeboom (1989). Comments by J. H. Schuenemeyer (1989) and R. Bargmann (1989) are briefly considered. (TJH)
Descriptors: Correlation, Factor Analysis, Generalization, Mathematical Models
Peer reviewed Peer reviewed
Clogg, Clifford C.; And Others – Journal of Educational Statistics, 1992
Methods for assessing collapsibility in regression problems are described, including possible extensions to the class of generalized linear models. These procedures, with terminology borrowed from the contingency table field, can be used in experimental settings or nonexperimental settings where two models viewed as alternative explanations are…
Descriptors: Comparative Analysis, Equations (Mathematics), Mathematical Models, Maximum Likelihood Statistics
Peer reviewed Peer reviewed
Muthen, Bengt; Lehman, James – Journal of Educational Statistics, 1985
The applicability of a new multiple-group factor analysis of dichotomous variables is shown and contrasted with the item response theory approach to item bias analysis. Situations are considered where the same set of test items has been administered to more than one group of examinees. (Author/BS).
Descriptors: Factor Analysis, Item Analysis, Latent Trait Theory, Mathematical Models
Peer reviewed Peer reviewed
Rachman-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 reviewed Peer reviewed
Joe, George W.; Mendoza, Jorge L. – Journal of Educational Statistics, 1989
The internal correlation--a measure of dependency in a set of variables--is discussed and generalized. Applications of the internal correlation coefficient and its generalizations are given for several data-analytic situations. The internal correlation is illustrated and the concept is expanded to a series of additional indices. (TJH)
Descriptors: Correlation, Equations (Mathematics), Factor Analysis, Generalization
Peer reviewed Peer reviewed
Rozeboom, William W. – Journal of Educational Statistics, 1989
Use of internal correlation for statistical analysis--proposed by G. W. Joe and J. L. Mendoza (1989)--is discussed. Focus is on the "content" question (what this application can do with the information that statistics contain) and the "eloquence" question (the advantages of this means of encoding information over other means). (TJH)
Descriptors: Correlation, Equations (Mathematics), Factor Analysis, Generalization
Peer reviewed Peer reviewed
Muthen, Bengt – Journal of Educational Statistics, 1985
Drawing on recently developed methodology for structural equation modeling with categorical data, this article proposes a new approach for investigating the behavior of dichotomously scored test items in relation to other relevant (observed) variables. A linear structural model relates the latent ability variable to a set of observed scores.…
Descriptors: Biology, Item Analysis, Latent Trait Theory, Mathematical Models
Peer reviewed Peer reviewed
Becker, Betsy Jane – Journal of Educational Statistics, 1992
Combining information to estimate standardized partial regression coefficients in a linear model is discussed. A combined estimate obtained from the pooled correlation matrix is proposed, and its large sample distribution is obtained. The method is generalized to handle a random effects model in which correlation parameters vary across studies.…
Descriptors: Correlation, Equations (Mathematics), Estimation (Mathematics), Hypothesis Testing
Peer reviewed Peer reviewed
Snijders, Tom A. B.; Bosker, Roel J. – Journal of Educational Statistics, 1993
Some approximate formulas are presented for standard errors of estimated regression coefficients in two-level designs. If the researcher can make a reasonable guess as to parameters occurring in the model, this approximation can be a guide to the choice of sample sizes at either level. (SLD)
Descriptors: Equations (Mathematics), Error of Measurement, Estimation (Mathematics), Mathematical Models
Peer reviewed Peer reviewed
Sparks, Ross S.; Ballantyne, Roy – Journal of Educational Statistics, 1990
Two models are presented to compare trainee and expert assessment strategies. The use of these procedures in assessment training programs is illustrated in a study of 5 postgraduate students in an environmental education course who were required to rate the work of 20 students. (SLD)
Descriptors: Comparative Analysis, Educational Assessment, Equations (Mathematics), Evaluation Methods
Peer reviewed Peer reviewed
Singer, Judith D.; Willett, John B. – Journal of Educational Statistics, 1993
Using longitudinal data on career paths of 3,941 special educators, maximum likelihood estimators are derived for the parameters of a discrete-time hazard model, and it is shown that the model can be fit using standard logistic regression software. Illustrative computer codes from the Statistical Analysis System (SAS) are offered. (SLD)
Descriptors: Elementary Secondary Education, Equations (Mathematics), Estimation (Mathematics), Life Events