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Stucky, Brian D.; Thissen, David; Edelen, Maria Orlando – Applied Psychological Measurement, 2013
Test developers often need to create unidimensional scales from multidimensional data. For item analysis, "marginal trace lines" capture the relation with the general dimension while accounting for nuisance dimensions and may prove to be a useful technique for creating short-form tests. This article describes the computations needed to obtain…
Descriptors: Test Construction, Test Length, Item Analysis, Item Response Theory
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Liu, Yang; Thissen, David – Applied Psychological Measurement, 2012
Local dependence (LD) refers to the violation of the local independence assumption of most item response models. Statistics that indicate LD between a pair of items on a test or questionnaire that is being fitted with an item response model can play a useful diagnostic role in applications of item response theory. In this article, a new score test…
Descriptors: Item Response Theory, Statistical Analysis, Models, Identification
Wainer, Howard; Thissen, David – 1985
Using simulated item response data, the performance of several "robust" and conventional schemes for ability estimation was evaluated in conjunction with logistic item response theory models (one, two, and three parameter models). The simulated item response data were generated using a model that is more complex than are the usual…
Descriptors: Adaptive Testing, Adults, Computer Assisted Testing, Error of Measurement
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Thissen, David – Measurement: Interdisciplinary Research and Perspectives, 2009
Maris and Bechger's article is an exercise in technical virtuosity and provides much to be learned by students of psychometrics. In this commentary, the author begins with making two observations. The first is that the title, "On Interpreting the Model Parameters for the Three Parameter Logistic Model," belies the generality of parts of Maris and…
Descriptors: Item Response Theory, Models, Selection
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Woods, Carol M.; Thissen, David – Psychometrika, 2006
The purpose of this paper is to introduce a new method for fitting item response theory models with the latent population distribution estimated from the data using splines. A spline-based density estimation system provides a flexible alternative to existing procedures that use a normal distribution, or a different functional form, for the…
Descriptors: Simulation, Population Distribution, Item Response Theory, Computation
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Thissen, David; Wainer, Howard – Journal of Educational Statistics, 1990
Confidence envelopes for one-parameter, two-parameter, and three-parameter logistic item response models are illustrated. M-line plots showing the genesis of the envelope and the density of lines in the confidence region are described and illustrated. (Author/SLD)
Descriptors: Equations (Mathematics), Graphs, Item Response Theory, Mathematical Models
Thissen, David; Wainer, Howard – 1983
A statistical method is described and illustrated which provides confidence envelopes around item response functions. Examples of 95 percent confidence envelopes for the one-, two-, and three-parameter logistic response models are given. In addition, the authors describe N-line plots, which show the genesis of the envelope as well as the density…
Descriptors: Graphs, Latent Trait Theory, Mathematical Formulas, Mathematical Models
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Thissen, David; Wainer, Howard – Psychometrika, 1982
The mathematics required to calculate the asymptotic standard errors of the parameters of three commonly used logistic item response models is described and used to generate values for common situations. Difficulties in using maximum likelihood estimation with the three parameter model are discussed. (Author/JKS)
Descriptors: Error of Measurement, Item Analysis, Latent Trait Theory, Maximum Likelihood Statistics
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Thissen, David – Psychometrika, 1982
Two algorithms for marginal maximum likelihood estimation for the Rasch model are provided. The more efficient of the two algorithms is extended to estimation for the linear logistic model. Numerical examples of both procedures are presented. (Author/JKS)
Descriptors: Algorithms, Estimation (Mathematics), Item Analysis, Latent Trait Theory