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Journal of Educational… | 4 |
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Dayton, C. Mitchell | 1 |
Macready, George B. | 1 |
McSweeney, Maryellen | 1 |
Rosenbaum, Paul R. | 1 |
Schmidt, William H. | 1 |
van der Linden, Wim J. | 1 |
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Journal Articles | 3 |
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Macready, George B.; Dayton, C. Mitchell – Journal of Educational Statistics, 1980
Data evolving from processes which are developmental or hierarchical in nature are often analyzed by using latent class or latent structure models. A procedure for estimating such models when the model is not "identifiable" is presented. (JKS)
Descriptors: Data Analysis, Developmental Psychology, Developmental Tasks, Mathematical Models

McSweeney, Maryellen; Schmidt, William H. – Journal of Educational Statistics, 1977
The relationship between quantitative predictor variables and the probability of occurrence of one or more levels of a qualitative criterion variable can be analyzed by quantal response techniques. This paper presents and discusses two quantal response models, comparing them to multiple linear regression and discriminant analysis. (Author/JKS)
Descriptors: Discriminant Analysis, Mathematical Models, Multiple Regression Analysis, Predictor Variables

van der Linden, Wim J. – Journal of Educational Statistics, 1978
Macready and Dayton introduced two probabilistic models for mastery assessment based on an idealistic all-or-none conception of mastery. Alternatively, an application of latent trait theory to mastery testing is proposed (a three parameter logistic model) as a more plausible model for test theory. (Author/CTM)
Descriptors: Criterion Referenced Tests, Guessing (Tests), Item Analysis, Latent Trait Theory

Rosenbaum, Paul R. – Journal of Educational Statistics, 1986
Using data from the High School and Beyond, this article presents statistical procedures to estimate the effect of dropping out of high school on cognitive achievement test scores. Each sampled dropout is matched to a student remaining in the same school. Methods for addressing the possible omission of covariates are described. (BS)
Descriptors: Achievement Tests, Analysis of Covariance, Dropouts, Effect Size