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de la Torre, Jimmy – Psychometrika, 2011
The G-DINA ("generalized deterministic inputs, noisy and gate") model is a generalization of the DINA model with more relaxed assumptions. In its saturated form, the G-DINA model is equivalent to other general models for cognitive diagnosis based on alternative link functions. When appropriate constraints are applied, several commonly used…
Descriptors: Structural Equation Models, Identification, Models, Comparative Analysis
Peeters, Carel F. W. – Psychometrika, 2012
In an addendum to his seminal 1969 article Joreskog stated two sets of conditions for rotational identification of the oblique factor solution under utilization of fixed zero elements in the factor loadings matrix (Joreskog in "Advances in factor analysis and structural equation models," pp. 40-43, 1979). These condition sets, formulated under…
Descriptors: Structural Equation Models, Factor Analysis, Correlation
Maydeu-Olivares, Alberto; Brown, Gregory – Psychometrika, 2013
We offer an introduction to the five papers that make up this special section. These papers deal with a range of the methodological challenges that face researchers analyzing fMRI data--the spatial, multilevel, and longitudinal nature of the data, the sources of noise, and so on. The papers all provide analyses of data collected by a multi-site…
Descriptors: Data Analysis, Measurement, Brain, Diagnostic Tests
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
Ranger, Jochen; Kuhn, Jorg-Tobias – Psychometrika, 2012
Latent trait models for response times in tests have become popular recently. One challenge for response time modeling is the fact that the distribution of response times can differ considerably even in similar tests. In order to reduce the need for tailor-made models, a model is proposed that unifies two popular approaches to response time…
Descriptors: Reaction Time, Tests, Models, Computation
Boker, Steven; Neale, Michael; Maes, Hermine; Wilde, Michael; Spiegel, Michael; Brick, Timothy; Spies, Jeffrey; Estabrook, Ryne; Kenny, Sarah; Bates, Timothy; Mehta, Paras; Fox, John – Psychometrika, 2011
OpenMx is free, full-featured, open source, structural equation modeling (SEM) software. OpenMx runs within the "R" statistical programming environment on Windows, Mac OS-X, and Linux computers. The rationale for developing OpenMx is discussed along with the philosophy behind the user interface. The OpenMx data structures are…
Descriptors: Structural Equation Models, Open Source Technology, Computer Software, Models
Huang, Guan-Hua; Wang, Su-Mei; Hsu, Chung-Chu – Psychometrika, 2011
Statisticians typically estimate the parameters of latent class and latent profile models using the Expectation-Maximization algorithm. This paper proposes an alternative two-stage approach to model fitting. The first stage uses the modified k-means and hierarchical clustering algorithms to identify the latent classes that best satisfy the…
Descriptors: Mathematics, Data Analysis, Classification, Models
Bocci, Laura; Vichi, Maurizio – Psychometrika, 2011
A weighted Euclidean distance model for analyzing three-way dissimilarity data (stimuli by stimuli by subjects) for heterogeneous subjects is proposed. First, it is shown that INDSCAL may fail to identify a common space representative of the observed data structure in presence of heterogeneity. A new model that removes the rotational invariance of…
Descriptors: Models, Data Analysis, Multidimensional Scaling
Gaer, Eva Vande; Ceulemans, Eva; Van Mechelen, Iven; Kuppens, Peter – Psychometrika, 2012
In many psychological research domains stimulus-response profiles are explained by conjecturing a sequential process in which some variables mediate between stimuli and responses. Charting sequential processes is often a complex task because (1) many possible mediating variables may exist, and (2) interindividual differences may occur in the…
Descriptors: Stimuli, Responses, Psychological Studies, Sequential Approach
Jennrich, Robert I.; Bentler, Peter M. – Psychometrika, 2012
Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger and Swineford ("Psychometrika" 47:41-54, 1937). The bi-factor model has a general factor, a number of group factors, and an explicit bi-factor structure. Jennrich and Bentler ("Psychometrika" 76:537-549, 2011) introduced an exploratory form of bi-factor…
Descriptors: Factor Structure, Factor Analysis, Models, Comparative Analysis
Bentler, Peter M.; de Leeuw, Jan – Psychometrika, 2011
When the factor analysis model holds, component loadings are linear combinations of factor loadings, and vice versa. This interrelation permits us to define new optimization criteria and estimation methods for exploratory factor analysis. Although this article is primarily conceptual in nature, an illustrative example and a small simulation show…
Descriptors: Factor Analysis, Models, Computation, Methods
Halpin, Peter F.; Dolan, Conor V.; Grasman, Raoul P. P. P.; De Boeck, Paul – Psychometrika, 2011
The relationship between linear factor models and latent profile models is addressed within the context of maximum likelihood estimation based on the joint distribution of the manifest variables. Although the two models are well known to imply equivalent covariance decompositions, in general they do not yield equivalent estimates of the…
Descriptors: Models, Maximum Likelihood Statistics, Computation, Goodness of Fit
Vasdekis, Vassilis G. S.; Cagnone, Silvia; Moustaki, Irini – Psychometrika, 2012
The paper proposes a composite likelihood estimation approach that uses bivariate instead of multivariate marginal probabilities for ordinal longitudinal responses using a latent variable model. The model considers time-dependent latent variables and item-specific random effects to be accountable for the interdependencies of the multivariate…
Descriptors: Geometric Concepts, Computation, Probability, Longitudinal Studies
McDonald, Roderick P. – Psychometrika, 2011
A distinction is proposed between measures and predictors of latent variables. The discussion addresses the consequences of the distinction for the true-score model, the linear factor model, Structural Equation Models, longitudinal and multilevel models, and item-response models. A distribution-free treatment of calibration and…
Descriptors: Measurement, Structural Equation Models, Item Response Theory, Error of Measurement
van der Ark, L. Andries; Bergsma, Wicher P. – Psychometrika, 2010
In contrast to dichotomous item response theory (IRT) models, most well-known polytomous IRT models do not imply stochastic ordering of the latent trait by the total test score (SOL). This has been thought to make the ordering of respondents on the latent trait using the total test score questionable and throws doubt on the justifiability of using…
Descriptors: Scores, Nonparametric Statistics, Item Response Theory, Models