esaBcv

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Author: Art B. Owen, Jingshu Wang
Contact: https://cran.r-project.org/web/packages/esaBcv/index.html
Description: esaBcv: Estimate Number of Latent Factors and Factor Matrix for Factor Analysis. These functions estimate the latent factors of a given matrix, no matter it is high-dimensional or not. It tries to first estimate the number of factors using bi-cross-validation and then estimate the latent factor matrix and the noise variances. For more information about the method, see Art B. Owen and Jingshu Wang 2015 archived article on factor model (http://arxiv.org/abs/1503.03515).
Analyses: DIF; Dimensionality; Factor/Latent Structure; Item & Test Analysis; Multidimensional Models; Person Fit/Cheating; Rater Effects; Scoring
System Requirements: Windows, Mac, Linux
Measurement Model: Latent Structure
License Type: Open-Source (R)
Documentation: user manual, simulated dataset

Software License
Open-Source (R)
Measurement Model
Latent Structure
Analysis
Differential Item Functioning; Dimensionality; Factor/Latent Structure; Item & Test Analysis; Multidimensional Models; Person Fit/Cheating; Rater Effects; Scoring