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Tijmstra, Jesper; Hessen, David J.; van der Heijden, Peter G. M.; Sijtsma, Klaas – Psychometrika, 2013
Most dichotomous item response models share the assumption of latent monotonicity, which states that the probability of a positive response to an item is a nondecreasing function of a latent variable intended to be measured. Latent monotonicity cannot be evaluated directly, but it implies manifest monotonicity across a variety of observed scores,…
Descriptors: Item Response Theory, Statistical Inference, Probability, Psychometrics
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Hamaker, E. L.; Grasman, R. P. P. P. – Psychometrika, 2012
Many psychological processes are characterized by recurrent shifts between distinct regimes or states. Examples that are considered in this paper are the switches between different states associated with premenstrual syndrome, hourly fluctuations in affect during a major depressive episode, and shifts between a "hot hand" and a…
Descriptors: Psychological Patterns, Statistical Inference, Data, Simulation
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Skrondal, Anders; Kuha, Jouni – Psychometrika, 2012
The likelihood for generalized linear models with covariate measurement error cannot in general be expressed in closed form, which makes maximum likelihood estimation taxing. A popular alternative is regression calibration which is computationally efficient at the cost of inconsistent estimation. We propose an improved regression calibration…
Descriptors: Computation, Maximum Likelihood Statistics, Error of Measurement, Regression (Statistics)
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Davis-Stober, Clintin P. – Psychometrika, 2011
Many researchers have demonstrated that fixed, exogenously chosen weights can be useful alternatives to Ordinary Least Squares (OLS) estimation within the linear model (e.g., Dawes, Am. Psychol. 34:571-582, 1979; Einhorn & Hogarth, Org. Behav. Human Perform. 13:171-192, 1975; Wainer, Psychol. Bull. 83:213-217, 1976). Generalizing the approach of…
Descriptors: Least Squares Statistics, Error of Measurement, Geometry, Computation
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Zhang, Guangjian; Preacher, Kristopher J.; Jennrich, Robert I. – Psychometrika, 2012
The infinitesimal jackknife, a nonparametric method for estimating standard errors, has been used to obtain standard error estimates in covariance structure analysis. In this article, we adapt it for obtaining standard errors for rotated factor loadings and factor correlations in exploratory factor analysis with sample correlation matrices. Both…
Descriptors: Factor Analysis, Maximum Likelihood Statistics, Error of Measurement, Nonparametric Statistics
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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
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Molenaar, Dylan; Dolan, Conor V.; de Boeck, Paul – Psychometrika, 2012
The Graded Response Model (GRM; Samejima, "Estimation of ability using a response pattern of graded scores," Psychometric Monograph No. 17, Richmond, VA: The Psychometric Society, 1969) can be derived by assuming a linear regression of a continuous variable, Z, on the trait, [theta], to underlie the ordinal item scores (Takane & de Leeuw in…
Descriptors: Simulation, Regression (Statistics), Psychometrics, Item Response Theory
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Yuan, Ke-Hai; Zhang, Zhiyong – Psychometrika, 2012
The paper develops a two-stage robust procedure for structural equation modeling (SEM) and an R package "rsem" to facilitate the use of the procedure by applied researchers. In the first stage, M-estimates of the saturated mean vector and covariance matrix of all variables are obtained. Those corresponding to the substantive variables…
Descriptors: Structural Equation Models, Tests, Federal Aid, Psychometrics
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Yuan, Ke-Hai; Chan, Wai – Psychometrika, 2011
The paper obtains consistent standard errors (SE) and biases of order O(1/n) for the sample standardized regression coefficients with both random and given predictors. Analytical results indicate that the formulas for SEs given in popular text books are consistent only when the population value of the regression coefficient is zero. The sample…
Descriptors: Statistical Bias, Error of Measurement, Regression (Statistics), Predictor Variables
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Bentler, Peter M.; Yuan, Ke-Hai – Psychometrika, 2011
Indefinite symmetric matrices that are estimates of positive-definite population matrices occur in a variety of contexts such as correlation matrices computed from pairwise present missing data and multinormal based methods for discretized variables. This note describes a methodology for scaling selected off-diagonal rows and columns of such a…
Descriptors: Scaling, Factor Analysis, Correlation, Predictor Variables
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Zhang, Guangjian; Chow, Sy-Miin; Ong, Anthony D. – Psychometrika, 2011
Structural equation models are increasingly used as a modeling tool for multivariate time series data in the social and behavioral sciences. Standard error estimators of SEM models, originally developed for independent data, require modifications to accommodate the fact that time series data are inherently dependent. In this article, we extend a…
Descriptors: Structural Equation Models, Simulation, Behavioral Sciences, Social Sciences
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Battauz, Michela; Bellio, Ruggero – Psychometrika, 2011
This paper proposes a structural analysis for generalized linear models when some explanatory variables are measured with error and the measurement error variance is a function of the true variables. The focus is on latent variables investigated on the basis of questionnaires and estimated using item response theory models. Latent variable…
Descriptors: Error of Measurement, Structural Equation Models, Computation, Item Response Theory
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Yuan, Ke-Hai; Cheng, Ying; Zhang, Wei – Psychometrika, 2010
This paper studies changes of standard errors (SE) of the normal-distribution-based maximum likelihood estimates (MLE) for confirmatory factor models as model parameters vary. Using logical analysis, simplified formulas and numerical verification, monotonic relationships between SEs and factor loadings as well as unique variances are found.…
Descriptors: Factor Analysis, Statistical Analysis, Error of Measurement, Models
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Draxler, Clemens – Psychometrika, 2010
This paper is concerned with supplementing statistical tests for the Rasch model so that additionally to the probability of the error of the first kind (Type I probability) the probability of the error of the second kind (Type II probability) can be controlled at a predetermined level by basing the test on the appropriate number of observations.…
Descriptors: Statistical Analysis, Probability, Sample Size, Error of Measurement
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Guo, Hongwen – Psychometrika, 2010
After many equatings have been conducted in a testing program, equating errors can accumulate to a degree that is not negligible compared to the standard error of measurement. In this paper, the author investigates the asymptotic accumulative standard error of equating (ASEE) for linear equating methods, including chained linear, Tucker, and…
Descriptors: Testing Programs, Testing, Error of Measurement, Equated Scores
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