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Gongjun Xu; Zhuoran Shang – Grantee Submission, 2018
This article focuses on a family of restricted latent structure models with wide applications in psychological and educational assessment, where the model parameters are restricted via a latent structure matrix to reflect prespecified assumptions on the latent attributes. Such a latent matrix is often provided by experts and assumed to be correct…
Descriptors: Psychological Evaluation, Educational Assessment, Item Response Theory, Models
Monroe, Scott; Cai, Li – Educational and Psychological Measurement, 2014
In Ramsay curve item response theory (RC-IRT) modeling, the shape of the latent trait distribution is estimated simultaneously with the item parameters. In its original implementation, RC-IRT is estimated via Bock and Aitkin's EM algorithm, which yields maximum marginal likelihood estimates. This method, however, does not produce the…
Descriptors: Item Response Theory, Models, Computation, Mathematics
Song, Hairong; Ferrer, Emilio – Structural Equation Modeling: A Multidisciplinary Journal, 2009
This article presents a state-space modeling (SSM) technique for fitting process factor analysis models directly to raw data. The Kalman smoother via the expectation-maximization algorithm to obtain maximum likelihood parameter estimates is used. To examine the finite sample properties of the estimates in SSM when common factors are involved, a…
Descriptors: Factor Analysis, Computation, Mathematics, Maximum Likelihood Statistics
Peer reviewedMaris, Eric; And Others – Psychometrika, 1996
Generalizing Boolean matrix decomposition to a larger class of matrix decomposition models is demonstrated, and probability matrix decomposition (PMD) models are introduced as a probabilistic version of the larger class. An algorithm is presented for the computation of maximum likelihood and maximum a posteriori estimates of the parameters of PMD…
Descriptors: Algorithms, Diagnostic Tests, Estimation (Mathematics), Matrices
Peer reviewedThomas, Neal; Gan, Nianci – Journal of Educational and Behavioral Statistics, 1997
Describes and assesses missing data methods currently used to analyze data from matrix sampling designs implemented by the National Assessment of Educational Progress. Several improved methods are developed, and these models are evaluated using an EM algorithm to obtain maximum likelihood estimates followed by multiple imputation of complete data…
Descriptors: Data Analysis, Item Response Theory, Matrices, Maximum Likelihood Statistics
Peer reviewedSwain, A. J. – Psychometrika, 1975
Considers a class of estimation procedures for the factor model. The procedures are shown to yield estimates possessing the same asymptotic sampling properties as those from estimation by maximum likelihood or generalized last squares, both special members of the class. General expressions for the derivatives needed for Newton-Raphson…
Descriptors: Factor Analysis, Least Squares Statistics, Matrices, Maximum Likelihood Statistics
Peer reviewedChen Shyuefee, Agnes; Michael, William B. – Educational and Psychological Measurement, 1993
Confirmatory maximum likelihood factor analysis determined how accurately each of several hypothesized combinations of first-order and higher-order factors reflecting creativity in the social intelligence of 192 high school students described the covariation in selected submatrixes from the total correlation matrix originally analyzed. Results…
Descriptors: Correlation, Creativity, Factor Structure, High School Students
Thompson, Bruce; And Others – 1993
Love is among the most fundamental aspects of the experience of being human, but measures of perceptions of the experience of love have only recently been explored. One of the most popular measures was developed by C. Hendrick and S. Hendrick. Most previous studies of the measure have used exploratory factor analysis and orthogonal factor…
Descriptors: Counseling, Factor Structure, Graduate Students, Higher Education

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