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Doran, Harold – Journal of Educational and Behavioral Statistics, 2023
This article is concerned with a subset of numerically stable and scalable algorithms useful to support computationally complex psychometric models in the era of machine learning and massive data. The subset selected here is a core set of numerical methods that should be familiar to computational psychometricians and considers whitening transforms…
Descriptors: Scaling, Algorithms, Psychometrics, Computation
Edgar C. Merkle; Oludare Ariyo; Sonja D. Winter; Mauricio Garnier-Villarreal – Grantee Submission, 2023
We review common situations in Bayesian latent variable models where the prior distribution that a researcher specifies differs from the prior distribution used during estimation. These situations can arise from the positive definite requirement on correlation matrices, from sign indeterminacy of factor loadings, and from order constraints on…
Descriptors: Models, Bayesian Statistics, Correlation, Evaluation Methods
Hua Ma; Wen Zhao; Yuqi Tang; Peiji Huang; Haibin Zhu; Wensheng Tang; Keqin Li – IEEE Transactions on Learning Technologies, 2024
To prevent students from learning risks and improve teachers' teaching quality, it is of great significance to provide accurate early warning of learning performance to students by analyzing their interactions through an e-learning system. In existing research, the correlations between learning risks and students' changing cognitive abilities or…
Descriptors: College Students, Learning Analytics, Learning Management Systems, Academic Achievement

Hanafi, Mohamed; ten Berge, Jos M. F. – Psychometrika, 2003
It is known that the Maxbet algorithm, which is an alternative to the method of generalized canonical correlation analysis and Procrustes analysis, may converge to local maxima. Discusses an eigenvalue criterion that is sufficient, but not necessary, for global optimality of the successive Maxbet algorithm. (SLD)
Descriptors: Algorithms, Correlation

Finkbeiner, C. T.; Tucker, L. R. – Psychometrika, 1982
The residual variance is often used as an approximation to the uniqueness in factor analysis. An upper bound approximation to the residual variance is presented for the case when the correlation matrix is singular. (Author/JKS)
Descriptors: Algorithms, Correlation, Factor Analysis, Matrices

Dolker, Michael; And Others – Psychometrika, 1982
Efron's Monte Carlo bootstrap algorithm is shown to cause degeneracies in Pearson's r for sufficiently small samples. Two ways of preventing this problem when programing the bootstrap of r are considered. (Author)
Descriptors: Algorithms, Computer Programs, Correlation, Sampling

Schuegraf, Ernst J.; van Bommel, Martin F. – Canadian Journal of Information and Library Science, 1993
Describes the design of an automatic indexing system that is based on statistical techniques and expert system technology. Highlights include system architecture; the derivation of topic indicators, including word frequency; experimental results using documents from ERIC; the effects of stemming; and the identification of characteristic…
Descriptors: Algorithms, Automatic Indexing, Computer Software Development, Correlation