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Direct linkFranz Classe; Christoph Kern – Educational and Psychological Measurement, 2024
We develop a "latent variable forest" (LV Forest) algorithm for the estimation of latent variable scores with one or more latent variables. LV Forest estimates unbiased latent variable scores based on "confirmatory factor analysis" (CFA) models with ordinal and/or numerical response variables. Through parametric model…
Descriptors: Algorithms, Item Response Theory, Artificial Intelligence, Factor Analysis
Hoang V. Nguyen; Niels G. Waller – Educational and Psychological Measurement, 2024
We conducted an extensive Monte Carlo study of factor-rotation local solutions (LS) in multidimensional, two-parameter logistic (M2PL) item response models. In this study, we simulated more than 19,200 data sets that were drawn from 96 model conditions and performed more than 7.6 million rotations to examine the influence of (a) slope parameter…
Descriptors: Monte Carlo Methods, Item Response Theory, Correlation, Error of Measurement
Peer reviewedHofmann, Richard J. – Educational and Psychological Measurement, 1978
A general factor analysis computer algorithm is briefly discussed. The algorithm is highly transportable with minimum limitations on the number of observations. Both singular and non-singular data can be analyzed. (Author/JKS)
Descriptors: Algorithms, Computer Programs, Factor Analysis, Transformations (Mathematics)
Peer reviewedHarris, Margaret L.; Harris, Chester W. – Educational and Psychological Measurement, 1971
Descriptors: Algorithms, Comparative Analysis, Factor Analysis, Factor Structure
