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Psychometrika

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https://www.readbyqxmd.com/read/28290111/generalized-network-psychometrics-combining-network-and-latent-variable-models
#1
Sacha Epskamp, Mijke Rhemtulla, Denny Borsboom
We introduce the network model as a formal psychometric model, conceptualizing the covariance between psychometric indicators as resulting from pairwise interactions between observable variables in a network structure. This contrasts with standard psychometric models, in which the covariance between test items arises from the influence of one or more common latent variables. Here, we present two generalizations of the network model that encompass latent variable structures, establishing network modeling as parts of the more general framework of structural equation modeling (SEM)...
March 13, 2017: Psychometrika
https://www.readbyqxmd.com/read/28290110/dealing-with-reflection-invariance-in-bayesian-factor-analysis
#2
Elena A Erosheva, S McKay Curtis
This paper considers the reflection unidentifiability problem in confirmatory factor analysis (CFA) and the associated implications for Bayesian estimation. We note a direct analogy between the multimodality in CFA models that is due to all possible column sign changes in the matrix of loadings and the multimodality in finite mixture models that is due to all possible relabelings of the mixture components. Drawing on this analogy, we derive and present a simple approach for dealing with reflection in variance in Bayesian factor analysis...
March 13, 2017: Psychometrika
https://www.readbyqxmd.com/read/28290109/continuous-online-item-calibration-parameter-recovery-and-item-utilization
#3
Hao Ren, Wim J van der Linden, Qi Diao
Parameter recovery and item utilization were investigated for different designs for online test item calibration. The design was adaptive in a double sense: it assumed both adaptive testing of examinees from an operational pool of previously calibrated items and adaptive assignment of field-test items to the examinees. Four criteria of optimality for the assignment of the field-test items were used, each of them based on the information in the posterior distributions of the examinee's ability parameter during adaptive testing as well as the sequentially updated posterior distributions of the field-test item parameters...
March 13, 2017: Psychometrika
https://www.readbyqxmd.com/read/28290108/some-improvements-in-confidence-intervals-for-standardized-regression-coefficients
#4
Paul Dudgeon
Yuan and Chan (Psychometrika 76:670-690, 2011. doi: 10.1007/S11336-011-9224-6 ) derived consistent confidence intervals for standardized regression coefficients under fixed and random score assumptions. Jones and Waller (Psychometrika 80:365-378, 2015. doi: 10.1007/S11336-013-9380-Y ) extended these developments to circumstances where data are non-normal by examining confidence intervals based on Browne's (Br J Math Stat Psychol 37:62-83, 1984. doi: 10.1111/j.2044-8317.1984.tb00789.x ) asymptotic distribution-free (ADF) theory...
March 13, 2017: Psychometrika
https://www.readbyqxmd.com/read/28247165/a-variational-maximization-maximization-algorithm-for-generalized-linear-mixed-models-with-crossed-random-effects
#5
Minjeong Jeon, Frank Rijmen, Sophia Rabe-Hesketh
We present a variational maximization-maximization algorithm for approximate maximum likelihood estimation of generalized linear mixed models with crossed random effects (e.g., item response models with random items, random raters, or random occasion-specific effects). The method is based on a factorized variational approximation of the latent variable distribution given observed variables, which creates a lower bound of the log marginal likelihood. The lower bound is maximized with respect to the factorized distributions as well as model parameters...
February 28, 2017: Psychometrika
https://www.readbyqxmd.com/read/28224368/generalized-fiducial-inference-for-logistic-graded-response-models
#6
Yang Liu, Jan Hannig
Samejima's graded response model (GRM) has gained popularity in the analyses of ordinal response data in psychological, educational, and health-related assessment. Obtaining high-quality point and interval estimates for GRM parameters attracts a great deal of attention in the literature. In the current work, we derive generalized fiducial inference (GFI) for a family of multidimensional graded response model, implement a Gibbs sampler to perform fiducial estimation, and compare its finite-sample performance with several commonly used likelihood-based and Bayesian approaches via three simulation studies...
February 21, 2017: Psychometrika
https://www.readbyqxmd.com/read/28213678/unifying-differential-item-functioning-in-factor-analysis-for-categorical-data-under-a-discretization-of-a-normal-variant
#7
Yu-Wei Chang, Nan-Jung Hsu, Rung-Ching Tsai
The multiple-group categorical factor analysis (FA) model and the graded response model (GRM) are commonly used to examine polytomous items for differential item functioning to detect possible measurement bias in educational testing. In this study, the multiple-group categorical factor analysis model (MC-FA) and multiple-group normal-ogive GRM models are unified under the common framework of discretization of a normal variant. We rigorously justify a set of identified parameters and determine possible identifiability constraints necessary to make the parameters just-identified and estimable in the common framework of MC-FA...
February 17, 2017: Psychometrika
https://www.readbyqxmd.com/read/28197969/functional-parallel-factor-analysis-for-functions-of-one-and-two-dimensional-arguments
#8
Ji Yeh Choi, Heungsun Hwang, Marieke E Timmerman
Parallel factor analysis (PARAFAC) is a useful multivariate method for decomposing three-way data that consist of three different types of entities simultaneously. This method estimates trilinear components, each of which is a low-dimensional representation of a set of entities, often called a mode, to explain the maximum variance of the data. Functional PARAFAC permits the entities in different modes to be smooth functions or curves, varying over a continuum, rather than a collection of unconnected responses...
February 14, 2017: Psychometrika
https://www.readbyqxmd.com/read/28194550/variance-based-cluster-selection-criteria-in-a-k-means-framework-for-one-mode-dissimilarity-data
#9
J Fernando Vera, Rodrigo Macías
One of the main problems in cluster analysis is that of determining the number of groups in the data. In general, the approach taken depends on the cluster method used. For K-means, some of the most widely employed criteria are formulated in terms of the decomposition of the total point scatter, regarding a two-mode data set of N points in p dimensions, which are optimally arranged into K classes. This paper addresses the formulation of criteria to determine the number of clusters, in the general situation in which the available information for clustering is a one-mode [Formula: see text] dissimilarity matrix describing the objects...
February 13, 2017: Psychometrika
https://www.readbyqxmd.com/read/28176040/assessing-the-size-of-model-misfit-in-structural-equation-models
#10
Alberto Maydeu-Olivares
When a statistically significant mean difference is found, the magnitude of the difference is judged qualitatively using an effect size such as Cohen's d. In contrast, in a structural equation model (SEM), the result of the statistical test of model fit is often disregarded if significant, and inferences are drawn using "close" models retained based on point estimates of sample statistics (goodness-of-fit indices). However, when a SEM cannot be retained using a test of exact fit, all substantive inferences drawn from it are suspect...
February 7, 2017: Psychometrika
https://www.readbyqxmd.com/read/28116569/erratum-to-linking-item-response-model-parameters
#11
Wim J van der Linden, Michelle D Barrett
No abstract text is available yet for this article.
January 23, 2017: Psychometrika
https://www.readbyqxmd.com/read/27044277/application-of-correlated-time-to-event-models-to-ecological-momentary-assessment-data
#12
Emily A Scherer, Lin Huang, Lydia A Shrier
Ecological momentary assessment data consist of in-the-moment sampling several times per day aimed at capturing phenomena that are highly variable. When research questions are focused on the association between a construct measured repeatedly and an event that occurs sporadically over time interspersed between repeated measures, the data consist of correlated observed or censored times to an event. In such a case, specialized time-to-event models that account for correlated observations are required to properly assess the relationships under study...
March 2017: Psychometrika
https://www.readbyqxmd.com/read/27924408/tackling-longitudinal-round-robin-data-a-social-relations-growth-model
#13
Steffen Nestler, Katharina Geukes, Roos Hutteman, Mitja D Back
The social relations model (SRM) is commonly used in the analysis of interpersonal judgments and behaviors that arise in groups. The SRM was developed only for use with cross-sectional data. Here, we introduce an extension of the SRM to longitudinal data. The social relations growth model represents a person's repeated SRM judgments of another person as a function of time. We show how the model's parameters can be estimated using restricted maximum likelihood, and how the effects of covariates on interindividual and interdyad variability in growth can be computed...
December 6, 2016: Psychometrika
https://www.readbyqxmd.com/read/27900637/commentaries-on-the-ten-most-highly-cited-psychometrika-articles-from-1936-to-the-present
#14
(no author information available yet)
No abstract text is available yet for this article.
December 2016: Psychometrika
https://www.readbyqxmd.com/read/27878414/a-creation-narrative-for-the-psychometric-society-and-psychometrika-in-the-beginning-there-was-paul-horst
#15
EDITORIAL
Willem Heiser, Lawrence Hubert
A review is provided for the creation of the Psychometric Society in 1935, and the establishment of its journal, Psychometrika, in 1936. This document is part of the 80th anniversary celebration for Psychometrika's founding, held during the annual meeting of the Psychometric Society in July of 2016 in Asheville, NC.
December 2016: Psychometrika
https://www.readbyqxmd.com/read/27873150/commemorating-the-80th-anniversary-of-the-founding-of-psychometrika-introduction-by-the-guest-editors
#16
EDITORIAL
Willem Heiser, Lawrence Hubert
No abstract text is available yet for this article.
December 2016: Psychometrika
https://www.readbyqxmd.com/read/27873149/erratum-to-quantifying-adventitious-error-in-a-covariance-structure-as-a-random-effect
#17
Hao Wu, Michael W Browne
No abstract text is available yet for this article.
December 2016: Psychometrika
https://www.readbyqxmd.com/read/27734298/joint-maximum-likelihood-estimation-for-diagnostic-classification-models
#18
Chia-Yi Chiu, Hans-Friedrich Köhn, Yi Zheng, Robert Henson
Joint maximum likelihood estimation (JMLE) is developed for diagnostic classification models (DCMs). JMLE has been barely used in Psychometrics because JMLE parameter estimators typically lack statistical consistency. The JMLE procedure presented here resolves the consistency issue by incorporating an external, statistically consistent estimator of examinees' proficiency class membership into the joint likelihood function, which subsequently allows for the construction of item parameter estimators that also have the consistency property...
December 2016: Psychometrika
https://www.readbyqxmd.com/read/27734297/covariate-free-and-covariate-dependent-reliability
#19
Peter M Bentler
Classical test theory reliability coefficients are said to be population specific. Reliability generalization, a meta-analysis method, is the main procedure for evaluating the stability of reliability coefficients across populations. A new approach is developed to evaluate the degree of invariance of reliability coefficients to population characteristics. Factor or common variance of a reliability measure is partitioned into parts that are, and are not, influenced by control variables, resulting in a partition of reliability into a covariate-dependent and a covariate-free part...
December 2016: Psychometrika
https://www.readbyqxmd.com/read/27734296/pairwise-likelihood-ratio-tests-and-model-selection-criteria-for-structural-equation-models-with-ordinal-variables
#20
Myrsini Katsikatsou, Irini Moustaki
Correlated multivariate ordinal data can be analysed with structural equation models. Parameter estimation has been tackled in the literature using limited-information methods including three-stage least squares and pseudo-likelihood estimation methods such as pairwise maximum likelihood estimation. In this paper, two likelihood ratio test statistics and their asymptotic distributions are derived for testing overall goodness-of-fit and nested models, respectively, under the estimation framework of pairwise maximum likelihood estimation...
December 2016: Psychometrika
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