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White, P. O. – Psychometrika, 1976
An alternative derivation is given for a generalization of the Rasch model which incorporates a guessing parameter. The probability of a correct response to the problem is a projective transformation of the problem difficulty. The ability and difficulty parameters separate into additive components. (Author/JKS)
Descriptors: Guessing (Tests), Mathematical Models, Measurement Techniques
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Collins, Linda M.; Cliff, Norman – Psychometrika, 1985
The axioms of a three-set Guttman simplex model are presented and the effects of relaxing the axioms for one of the three sets are examined. This model can be used to define longitudinal developmental scales. (NSF)
Descriptors: Mathematical Models, Measurement Techniques, Scaling, Test Construction
Peer reviewed Peer reviewed
Ramsay, J. O. – Psychometrika, 1978
Techniques are developed for constructing confidence regions for each of the points in a multidimensional scaling solution. Bayesian credibility regions are discussed, and a technique for displaying these regions is described. (Author/JKS)
Descriptors: Bayesian Statistics, Hypothesis Testing, Mathematical Models, Measurement Techniques
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Rindskopf, David – Psychometrika, 1983
Various models have been proposed for analyzing dichotomous test or questionnaire items which were constructed to reflect an assumed underlying structure (e.g., hierarchical). This paper shows that many such models are special cases of latent class analysis and discusses a currently available computer program to analyze them. (Author/JKS)
Descriptors: Computer Programs, Item Analysis, Mathematical Models, Measurement Techniques
Peer reviewed Peer reviewed
Frijters, J. E. R. – Psychometrika, 1981
The Triangular Constant Method was designed for the measurement of discriminability between sensory stimuli. Its original model assumes a steady excitatory detection state. The purpose of this paper is to elaborate on the consequences of assuming a variable exicitatory state and to formulate the concomitant model. (Author)
Descriptors: Data Analysis, Mathematical Models, Measurement Techniques, Perception
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Nishisato, Shizuhiko – Psychometrika, 1978
An alternative formulation for Guttman scaling is presented. The new formulation is described, and advantages over Guttman's formulation are detailed. The method is assumption-free and capable of multidimensional analysis. (Author/JKS)
Descriptors: Individual Differences, Mathematical Models, Measurement Techniques, Multidimensional Scaling
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Clogg, Clifford C.; Goodman, Leo A. – Psychometrika, 1986
Statistical methods are presented to facilitate a more complete analysis of results obtained when a scaling model is applied to data from two or more groups. Various kinds of scaling models are considered here in the multiple-group context. (Author/LMO)
Descriptors: Mathematical Models, Measurement Techniques, Response Style (Tests), Scaling
Peer reviewed Peer reviewed
Schonemann, Peter H. – Psychometrika, 1972
Paper shows that an obvious generalization of the subjective metrics model by Bloxom, Horan, Carroll and Chang has a very simple algebraic solution which was previously considered by Meredith in a different context. (Author)
Descriptors: Algebra, Analytic Geometry, Mathematical Models, Measurement Techniques
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Weeks, David G.; Bentler, P.M. – Psychometrika, 1982
Restricted multidimensional scaling models, allowing constraints on parameters, are extended to the case of asymmetric data. Examples of several models are provided, using journal citation data. Possible extensions of the models are considered. (Author/JKS)
Descriptors: Bibliographic Coupling, Data Analysis, Mathematical Models, Matrices
Peer reviewed Peer reviewed
Ramsay, J. O. – Psychometrika, 1980
In studies involving judgments of similarity or dissimilarity, a variety of other variables may also be measured. In such cases, there are important advantages to joint analyses of the dissimilarity and collateral variables. A variety of models are described for relating these and algorithms are described for fitting these to data. (Author/JKS)
Descriptors: Data Analysis, Guessing (Tests), Mathematical Models, Measurement Techniques
Peer reviewed Peer reviewed
Embretson, Susan E. – Psychometrika, 1991
A multidimensional model is presented for measuring learning and change based on item response theory. The model specifies a Wiener simplex pattern for involvement of initial ability and one or more modifiabilities in response potential for successive measurement occasions. Properties of the model are explored for several classical issues. (SLD)
Descriptors: Ability, Change, Equations (Mathematics), Item Response Theory
Peer reviewed Peer reviewed
Bechtel, Gordon G.; And Others – Psychometrika, 1971
Contains a solution for the multidimensional scaling of pairwise choice when individuals are represented as dimensional weights. The analysis supplies an exact least squares solution and estimates of group unscalability parameters. (DG)
Descriptors: Data Analysis, Mathematical Models, Measurement Techniques, Multidimensional Scaling
Peer reviewed Peer reviewed
Lord, Frederic M. – Psychometrika, 1971
A two-stage testing procedure, a routing test followed by one of several alternative second-stage tests, is studied in the situation where the purpose is measurement, not classification. Models are developed, examined, and compared with conventional tests and up-and-down procedures. (DG)
Descriptors: Guessing (Tests), Mathematical Models, Measurement Techniques, Scoring
Peer reviewed Peer reviewed
Langeheine, Rolf – Psychometrika, 1982
The degree to which Procrustean Individual Differences Scaling can be extended to related topics such as target analysis is discussed and a Monte Carlo study investigating the fit of the model under various conditions is presented. (JKS)
Descriptors: Data Analysis, Goodness of Fit, Individual Differences, Mathematical Models
Peer reviewed Peer reviewed
Meredith, William; Millsap, Roger E. – Psychometrika, 1992
A unified treatment is presented for conditions that should allow detection of measurement bias using statistical procedures involving only observed or manifest variables. Computational results demonstrate that methods for studying bias that rely exclusively on manifest variables are not generally diagnostic of the presence or absence of…
Descriptors: Bayesian Statistics, Equations (Mathematics), Identification, Item Bias
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