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Chen, Haiwen; Holland, Paul – Psychometrika, 2010
In this paper, we develop a new curvilinear equating for the nonequivalent groups with anchor test (NEAT) design under the assumption of the classical test theory model, that we name curvilinear Levine observed score equating. In fact, by applying both the kernel equating framework and the mean preserving linear transformation of…
Descriptors: Equated Scores, Test Theory, Test Construction, Guidelines
Revelle, William; Zinbarg, Richard E. – Psychometrika, 2009
There are three fundamental problems in Sijtsma ("Psychometrika," 2008): (1) contrary to the name, the glb is not the greatest lower bound of reliability but rather is systematically less than omega[subscript t] (McDonald, "Test theory: A unified treatment," Erlbaum, Hillsdale, 1999), (2) we agree with Sijtsma that when considering how well a test…
Descriptors: Test Theory, Computer Software, Reliability
Borsboom, Denny – Psychometrika, 2006
This paper analyzes the theoretical, pragmatic, and substantive factors that have hampered the integration between psychology and psychometrics. Theoretical factors include the operationalist mode of thinking which is common throughout psychology, the dominance of classical test theory, and the use of "construct validity" as a catch-all category…
Descriptors: Psychometrics, Psychology, Test Theory, Construct Validity

McDonald, Roderick P. – Psychometrika, 1986
There is a unity underlying the diversity of models for the analysis of multivariate data. Essentially, they constitute a family of models, most generally nonlinear, for structural/functional relations between variables drawn from a behavior domain. (Author)
Descriptors: Factor Analysis, Generalizability Theory, Latent Trait Theory, Mathematical Models

de Gruijter, Data N. M. – Psychometrika, 1985
A simplification of Lord and Wingersky's method for computing the asymptotic variance-covariance matrix of maximum likelihood estimates for item and person parameters under some restrictions on the estimates is presented. Computation of the error variance-covariance matrix for the item parameters in the Rasch model is described. (NSF)
Descriptors: Error of Measurement, Latent Trait Theory, Matrices, Maximum Likelihood Statistics

Molenaar, Ivo W. – Psychometrika, 1983
Goodness of fit tests for the Rasch model are typically large-sample, global measures. This paper offers suggestions for small-sample exploratory techniques for examining the fit of item data to the Rasch model. (Author/JKS)
Descriptors: Goodness of Fit, Hypothesis Testing, Item Analysis, Latent Trait Theory

Holland, Paul W. – Psychometrika, 1981
Deciding whether sets of test data are consistent with any of a large class of item response models is considered. The assumption of local independence is weakened to a new condition, local nonnegative dependence (LND). Necessary and sufficient conditions are derived for a LND item response model. (Author/JKS)
Descriptors: Item Analysis, Latent Trait Theory, Mathematical Models, Psychometrics

Rost, Jurgen – Psychometrika, 1985
A latent class model for rating data is presented which provides an alternative to the latent trait approach of analyzing test data. It is the analog of Andrich's binomial Rasch model for Lazarsfeld's latent class analysis (LCA). Response probabilities for rating categories follow a binomial distribution and depend on class-specific item…
Descriptors: Item Analysis, Latent Trait Theory, Mathematical Models, Rating Scales

Jarjoura, David – Psychometrika, 1983
The problem of predicting universe scores for samples of examinees based on their responses to samples of items is treated. The measurement model categorizes items according to the cells of a table of test specifications, and the linear function derived for minimizing error variance in prediction uses responses to these categories. (Author/JKS)
Descriptors: Error of Measurement, Generalizability Theory, Item Sampling, Prediction

Masters, Geofferey N. – Psychometrika, 1985
Latent trait and latent class analyses of Likert-type data are compared. Key similarities and differences between these methods are described and illustrated by applying a latent trait model and a latent class model to the analysis of a set of "life satisfaction" data. (Author/NSF)
Descriptors: Attitude Measures, Goodness of Fit, Latent Trait Theory, Mathematical Models

Fischer, Gerhard H. – Psychometrika, 1983
Two linearly constrained models based on the Rasch model are discussed. Necessary and sufficient conditions for the existence of unique conditional maximum likelihood estimators are derived. Methods for hypothesis testing within this framework are proposed. (Author/JKS)
Descriptors: Estimation (Mathematics), Hypothesis Testing, Latent Trait Theory, Mathematical Models

Andersen, Erling B. – Psychometrika, 1985
A model for longitudinal latent structure analysis was proposed that combined the values of a latent variable at two time points in a two-dimensional latent density. The correlation coefficient between the two values of the latent variable can then be estimated. (NSF)
Descriptors: Correlation, Latent Trait Theory, Mathematical Models, Maximum Likelihood Statistics

Yen, Wendy M. – Psychometrika, 1983
Tau-equivalence means that two tests produce equal true scores for individuals but that the distribution of errors for the tests could be different. This paper examines the effect of performing equipercentile equating techniques on tau-equivalent tests. (JKS)
Descriptors: Equated Scores, Latent Trait Theory, Psychometrics, Scores

Stegelmann, Werner – Psychometrika, 1983
The Rasch model is generalized to a multicomponent model, so that observations of component events are not needed to apply the model. It is shown that the generalized model maintains the property of specific objectivity of the Rasch model. An application to a mathematics test is provided. (Author/JKS)
Descriptors: Estimation (Mathematics), Item Analysis, Latent Trait Theory, Mathematical Models

Andrich, David – Psychometrika, 1995
This book discusses adapting pencil-and-paper tests to computerized testing. Mention is made of models for graded responses to items and of possibilities beyond pencil-and-paper-tests, but the book is essentially about dichotomously scored test items. Contrasts between item response theory and classical test theory are described. (SLD)
Descriptors: Adaptive Testing, Computer Assisted Testing, Item Response Theory, Scores