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Zhang, Zhiyong; Wang, Lijuan – Psychometrika, 2013

Despite wide applications of both mediation models and missing data techniques, formal discussion of mediation analysis with missing data is still rare. We introduce and compare four approaches to dealing with missing data in mediation analysis including list wise deletion, pairwise deletion, multiple imputation (MI), and a two-stage maximum…

Descriptors: Maximum Likelihood Statistics, Structural Equation Models, Simulation, Measurement Techniques

Wilson, Mark – Psychometrika, 2013

In this paper, I will review some aspects of psychometric projects that I have been involved in, emphasizing the nature of the work of the psychometricians involved, especially the balance between the statistical and scientific elements of that work. The intent is to seek to understand where psychometrics, as a discipline, has been and where it…

Descriptors: Psychometrics, Intellectual Disciplines, Periodicals, Statistics

Hwang, Heungsun; Suk, Hye Won; Lee, Jang-Han; Moskowitz, D. S.; Lim, Jooseop – Psychometrika, 2012

We propose a functional version of extended redundancy analysis that examines directional relationships among several sets of multivariate variables. As in extended redundancy analysis, the proposed method posits that a weighed composite of each set of exogenous variables influences a set of endogenous variables. It further considers endogenous…

Descriptors: Redundancy, Psychometrics, Computation, Least Squares Statistics

Keller, Bryan – Psychometrika, 2012

Randomization tests are often recommended when parametric assumptions may be violated because they require no distributional or random sampling assumptions in order to be valid. In addition to being exact, a randomization test may also be more powerful than its parametric counterpart. This was demonstrated in a simulation study which examined the…

Descriptors: Statistical Analysis, Nonparametric Statistics, Simulation, Sampling

Tchumtchoua, Sylvie; Dey, Dipak K. – Psychometrika, 2012

This paper proposes a semiparametric Bayesian framework for the analysis of associations among multivariate longitudinal categorical variables in high-dimensional data settings. This type of data is frequent, especially in the social and behavioral sciences. A semiparametric hierarchical factor analysis model is developed in which the…

Descriptors: Factor Analysis, Bayesian Statistics, Behavioral Sciences, Social Sciences

Holling, Heinz; Bohning, Walailuck; Bohning, Dankmar – Psychometrika, 2012

Meta-analysis of diagnostic studies experience the common problem that different studies might not be comparable since they have been using a different cut-off value for the continuous or ordered categorical diagnostic test value defining different regions for which the diagnostic test is defined to be positive. Hence specificities and…

Descriptors: Diagnostic Tests, Accuracy, Nonparametric Statistics, Meta Analysis

Hwang, Heungsun; Jung, Kwanghee; Takane, Yoshio; Woodward, Todd S. – Psychometrika, 2012

We propose functional multiple-set canonical correlation analysis for exploring associations among multiple sets of functions. The proposed method includes functional canonical correlation analysis as a special case when only two sets of functions are considered. As in classical multiple-set canonical correlation analysis, computationally, the…

Descriptors: Multivariate Analysis, Computation, Data Analysis, Short Term Memory

van der Linden, Wim J. – Psychometrika, 2012

The issue of compensation in multidimensional response modeling is addressed. We show that multidimensional response models are compensatory in their ability parameters if and only if they are monotone. In addition, a minimal set of assumptions is presented under which the MLEs of the ability parameters are also compensatory. In a recent series of…

Descriptors: Models, Maximum Likelihood Statistics, Scoring

Hsieh, Fushing; Ferrer, Emilio; Chen, Shuchun; Mauss, Iris B.; John, Oliver; Gross, James J. – Psychometrika, 2011

We present an approach for evaluating coherence in multivariate systems that considers all the variables simultaneously. We operationalize the multivariate system as a network and define coherence as the efficiency with which a signal is transmitted throughout the network. We illustrate this approach with time series data from 15…

Descriptors: Multivariate Analysis, Emotional Response, Networks, Efficiency

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

Zhang, Jinming; Xie, Minge; Song, Xiaolan; Lu, Ting – Psychometrika, 2011

Asymptotic expansions of the maximum likelihood estimator (MLE) and weighted likelihood estimator (WLE) of an examinee's ability are derived while item parameter estimators are treated as covariates measured with error. The asymptotic formulae present the amount of bias of the ability estimators due to the uncertainty of item parameter estimators.…

Descriptors: Computation, Ability, Maximum Likelihood Statistics, Bias

ten Berge, Jos M. F. – Psychometrika, 2011

Matrices can be diagonalized by singular vectors or, when they are symmetric, by eigenvectors. Pairs of square matrices often admit simultaneous diagonalization, and always admit block wise simultaneous diagonalization. Generalizing these possibilities to more than two (non-square) matrices leads to methods of simplifying three-way arrays by…

Descriptors: Matrices, Transformations (Mathematics), Geometric Concepts

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

Waller, Niels; Jones, Jeff – Psychometrika, 2011

We describe methods for assessing all possible criteria (i.e., dependent variables) and subsets of criteria for regression models with a fixed set of predictors, x (where x is an n x 1 vector of independent variables). Our methods build upon the geometry of regression coefficients (hereafter called regression weights) in n-dimensional space. For a…

Descriptors: Criteria, Regression (Statistics), Correlation, Models

Linting, Marielle; van Os, Bart Jan; Meulman, Jacqueline J. – Psychometrika, 2011

In this paper, the statistical significance of the contribution of variables to the principal components in principal components analysis (PCA) is assessed nonparametrically by the use of permutation tests. We compare a new strategy to a strategy used in previous research consisting of permuting the columns (variables) of a data matrix…

Descriptors: Intervals, Simulation, Statistical Significance, Factor Analysis