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Lyrica Lucas; Anum Khushal; Robert Mayes; Brian A. Couch; Joseph Dauer – International Journal of Science Education, 2025
Educational reform priorities such as emphasis on quantitative modelling (QM) have positioned undergraduate biology instructors as designers of QM experiences to engage students in authentic science practices that support the development of data-driven and evidence-based reasoning. Yet, little is known about how biology instructors adapt to the…
Descriptors: Undergraduate Students, College Science, Biology, Classroom Observation Techniques
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Brogden, H. E. – Psychometrika, 1977
Relationships between the Rasch test analysis model, the law of comparative judgment, and additive conjoint measurement are discussed. (Author/JKS)
Descriptors: Comparative Analysis, Mathematical Models, Measurement, Test Interpretation
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Woodhouse, Brian; Jackson, Paul H. – Psychometrika, 1977
Finding and interpreting lower bounds for reliability coefficients for tests with non-homogeneous items has been a problem for psychometricians. A computer search procedure is developed for locating such a lower bound in a variety of settings. (Author/JKS)
Descriptors: Computer Programs, Mathematical Models, Measurement, Test Interpretation
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Zhang, Jinming; Stout, William – Psychometrika, 1997
Three counterexamples demonstrate that the Dutch Identity conjecture of P. Holland about examinee ability (1990) does not hold in general. The counterexamples suggest that only under strong assumptions can it be true that the limits of log-manifest probabilities are quadratic. Three propositions giving such strong conditions are given. (Author/SLD)
Descriptors: Ability, Item Response Theory, Mathematical Models, Probability
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Jackson, Paul H.; Agunwamba, Christian C. – Psychometrika, 1977
Finding and interpreting lower bounds for reliability coefficients for tests with nonhomogenous items has been a problem for psychometricians. This paper presents a mathematical formula for finding the greatest lower bound for such a coefficient. (Author/JKS)
Descriptors: Comparative Analysis, Mathematical Models, Measurement, Test Interpretation
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Sachan, Ronaldo – Psychometrika, 1984
A general class of differentiation indices is introduced for profiles of scores. Their ordinal properties and an application to Holland's classification system are examined. Comparison with other suggested indices is performed both theoretically and empirically. (Author)
Descriptors: Interest Inventories, Mathematical Models, Profiles, Proof (Mathematics)
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Andrich, David – Psychometrika, 1978
A rating response mechanism for ordered categories such as in Likert scaling, which is related to the traditional threshold formulation but distinctively different from it, is formulated. The mechanism is based on the Rasch model. Two parameters in addition to the usual Rasch parameters are identified and discussed. (Author/JKS)
Descriptors: Item Analysis, Mathematical Models, Psychometrics, Rating Scales
Bowling, John – 1993
Recent empirical studies of actual research practice demonstrate that general linear models, such as regression, have become increasingly popular. The present paper explores issues related to the interpretation of regression results, with illustrations drawn from studies in the counseling psychology literature. The primary focus of this paper is…
Descriptors: Counseling Psychology, Literature Reviews, Mathematical Models, Predictor Variables
Boldt, Robert F. – 1972
The Rasch model and other latent trait models encounter some difficulty when faced with an appreciable amount of missing data or omitting behavior. The present note assumes that some reasonable missing data model has been formulated which does not involve the parameters associated with the latent ability of interest. A maximum likelihood function…
Descriptors: Data Analysis, Item Analysis, Mathematical Models, Measurement Techniques
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Skinner, Harvey A. – Educational and Psychological Measurement, 1978
The concepts of elevation, scatter, and shape are investigated as parameters in assessing the similarity among profiles of individuals. A computational strategy for differentiating the independent contribution of each parameter to more global indices of resemblance is presented. (Author/JKS)
Descriptors: Data Analysis, Error of Measurement, Mathematical Models, Measurement Techniques
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Huynh, Huynh – Psychometrika, 1977
A model for the setting of mastery cut scores is presented. The model, based on the beta-binomial test distribution, allows for hand calculation of cut scores. The model provides a simple way to explore the consequences of selecting a particular cut score. (Author/JKS)
Descriptors: Career Development, Cutting Scores, Mastery Tests, Mathematical Models
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Lindsay, Carl A.; Prichard, Mark A. – Journal of Educational Measurement, 1971
Descriptors: Equated Scores, Goodness of Fit, Mathematical Models, Scores
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Cudeck, Robert – Multivariate Behavioral Research, 1982
Many models have been proposed for examining factors from several batteries of tests. A model for such an analysis is presented which allows for maintaining the distinction among batteries. A discussion of the computational procedures is given, and examples are provided. (Author/JKS)
Descriptors: Correlation, Data Analysis, Factor Analysis, Mathematical Models
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Nandakumar, Ratna – Multivariate Behavioral Research, 1993
The methodology of P. E. Holland and P. R. Rosenbaum (1986) to assess unidimensionality of binary data is outlined and illustrated through a simulation with 36 items for 2,000 examinees. How to interpret the results is discussed. (SLD)
Descriptors: Computer Simulation, Educational Assessment, Equations (Mathematics), Mathematical Models
Harris, Richard J. – 1992
Interpretation of emergent variables on the basis of structure coefficients (zero order correlations between original and emergent variables) is potentially very misleading and should be avoided in favor of interpretation on the basis of scoring coefficients. This is most apparent in multiple regression analysis and its special case, two-group…
Descriptors: Correlation, Discriminant Analysis, Mathematical Models, Multiple Regression Analysis
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