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Magis, David; Raiche, Gilles – Psychometrika, 2012
This paper focuses on two estimators of ability with logistic item response theory models: the Bayesian modal (BM) estimator and the weighted likelihood (WL) estimator. For the BM estimator, Jeffreys' prior distribution is considered, and the corresponding estimator is referred to as the Jeffreys modal (JM) estimator. It is established that under…
Descriptors: Item Response Theory, Computation, Bayesian Statistics, Models
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Jordan, Pascal; Spiess, Martin – Psychometrika, 2012
Maximum likelihood and Bayesian ability estimation in multidimensional item response models can lead to paradoxical results as proven by Hooker, Finkelman, and Schwartzman ("Psychometrika" 74(3): 419-442, 2009): Changing a correct response on one item into an incorrect response may produce a higher ability estimate in one dimension.…
Descriptors: Item Response Theory, Statistical Analysis, Factor Analysis, Generalization
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Grasshoff, Ulrike; Holling, Heinz; Schwabe, Rainer – Psychometrika, 2012
In this paper, optimal designs will be derived for estimating the ability parameters of the Rasch model when difficulty parameters are known. It is well established that a design is locally D-optimal if the ability and difficulty coincide. But locally optimal designs require that the ability parameters to be estimated are known. To attenuate this…
Descriptors: Item Response Theory, Test Items, Psychometrics, Statistical Analysis
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San Martin, Ernesto; Jara, Alejandro; Rolin, Jean-Marie; Mouchart, Michel – Psychometrika, 2011
We study the identification and consistency of Bayesian semiparametric IRT-type models, where the uncertainty on the abilities' distribution is modeled using a prior distribution on the space of probability measures. We show that for the semiparametric Rasch Poisson counts model, simple restrictions ensure the identification of a general…
Descriptors: Identification, Probability, Item Response Theory, Bayesian Statistics
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Tijmstra, Jesper; Hessen, David J.; van der Heijden, Peter G. M.; Sijtsma, Klaas – Psychometrika, 2011
A new observable consequence of the property of invariant item ordering is presented, which holds under Mokken's double monotonicity model for dichotomous data. The observable consequence is an invariant ordering of the item-total regressions. Kendall's measure of concordance "W" and a weighted version of this measure are proposed as measures for…
Descriptors: Item Response Theory, Bayesian Statistics, Regression (Statistics), Models
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Geerlings, Hanneke; Glas, Cees A. W.; van der Linden, Wim J. – Psychometrika, 2011
An application of a hierarchical IRT model for items in families generated through the application of different combinations of design rules is discussed. Within the families, the items are assumed to differ only in surface features. The parameters of the model are estimated in a Bayesian framework, using a data-augmented Gibbs sampler. An obvious…
Descriptors: Simulation, Intelligence Tests, Item Response Theory, Models
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Ligtvoet, Rudy – Psychometrika, 2012
In practice, the sum of the item scores is often used as a basis for comparing subjects. For items that have more than two ordered score categories, only the partial credit model (PCM) and special cases of this model imply that the subjects are stochastically ordered on the common latent variable. However, the PCM is very restrictive with respect…
Descriptors: Simulation, Item Response Theory, Comparative Analysis, Scores
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Morey, Richard D.; Rouder, Jeffrey N.; Speckman, Paul L. – Psychometrika, 2009
Human abilities in perceptual domains have conventionally been described with reference to a threshold that may be defined as the maximum amount of stimulation which leads to baseline performance. Traditional psychometric links, such as the probit, logit, and "t", are incompatible with a threshold as there are no true scores corresponding to…
Descriptors: Psychometrics, Computation, Item Response Theory, Models
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Yang, Mingan; Dunson, David B. – Psychometrika, 2010
Structural equation models (SEMs) with latent variables are widely useful for sparse covariance structure modeling and for inferring relationships among latent variables. Bayesian SEMs are appealing in allowing for the incorporation of prior information and in providing exact posterior distributions of unknowns, including the latent variables. In…
Descriptors: Structural Equation Models, Markov Processes, Item Response Theory, Bayesian Statistics
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Hooker, Giles; Finkelman, Matthew – Psychometrika, 2010
Hooker, Finkelman, and Schwartzman ("Psychometrika," 2009, in press) defined a paradoxical result as the attainment of a higher test score by changing answers from correct to incorrect and demonstrated that such results are unavoidable for maximum likelihood estimates in multidimensional item response theory. The potential for these results to…
Descriptors: Models, Scores, Item Response Theory, Psychometrics
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Klauer, Karl Christoph – Psychometrika, 2010
Multinomial processing tree models are widely used in many areas of psychology. A hierarchical extension of the model class is proposed, using a multivariate normal distribution of person-level parameters with the mean and covariance matrix to be estimated from the data. The hierarchical model allows one to take variability between persons into…
Descriptors: Simulation, Bayesian Statistics, Computation, Models
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Miyazaki, Kei; Hoshino, Takahiro – Psychometrika, 2009
In Item Response Theory (IRT), item characteristic curves (ICCs) are illustrated through logistic models or normal ogive models, and the probability that examinees give the correct answer is usually a monotonically increasing function of their ability parameters. However, since only limited patterns of shapes can be obtained from logistic models…
Descriptors: Nonverbal Communication, Probability, Item Response Theory, Bayesian Statistics
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Cao, Jing; Stokes, S. Lynne – Psychometrika, 2008
According to the recent Nation's Report Card, 12th-graders failed to produce gains on the 2005 National Assessment of Educational Progress (NAEP) despite earning better grades on average. One possible explanation is that 12th-graders were not motivated taking the NAEP, which is a low-stakes test. We develop three Bayesian IRT mixture models to…
Descriptors: Test Items, Simulation, National Competency Tests, Item Response Theory
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Rouder, Jeffrey N.; Lu, Jun; Sun, Dongchu; Speckman, Paul; Morey, Richard; Naveh-Benjamin, Moshe – Psychometrika, 2007
The theory of signal detection is convenient for measuring mnemonic ability in recognition memory paradigms. In these paradigms, randomly selected participants are asked to study randomly selected items. In practice, researchers aggregate data across items or participants or both. The signal detection model is nonlinear; consequently, analysis…
Descriptors: Simulation, Recognition (Psychology), Computation, Mnemonics
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Lee, Sik-Yum; Song, Xin-Yuan – Psychometrika, 2003
Proposed a new nonlinear structural equation model with fixed covariates to deal with some complicated substantive theory and developed a Bayesian path sampling procedure for model comparison. Illustrated the approach with an illustrative example using data from an international study. (SLD)
Descriptors: Bayesian Statistics, Comparative Analysis, Sampling, Structural Equation Models
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