R package psych: Procedures for Psychological, Psychometric, and Personality Research , A number of routines for personality, psychometrics and experimental psychology. Functions are primarily for scale construction using factor analysis, cluster analysis and reliability analysis, although others provide basic descriptive statistics. Item Response Theory is done using factor analysis of tetrachoric and polychoric correlations. Functions for simulating particular item and test structures are included. Several functions serve as a useful front end for structural equation modeling. Graphical displays of path diagrams, factor analysis and structural equation models are created using basic graphics. Some of the functions are written to support a book on psychometrics as well as publications in personality research. For more information, see the webpage. (Source:

References in zbMATH (referenced in 35 articles )

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  1. Daniel Ludecke; Mattan S. Ben-Shachar; Indrajeet Patil; Dominique Makowski: Extracting, Computing and Exploring the Parameters of Statistical Models using R (2020) not zbMATH
  2. Epskamp, Sacha: Psychometric network models from time-series and panel data (2020)
  3. Keith Goldfeld; Jacob Wujciak-Jens: simstudy: Illuminating research methods through data generation (2020) not zbMATH
  4. Markus D. Steiner; Silvia Grieder: EFAtools: An R package with fast and exible implementations of exploratory factor analysis tools (2020) not zbMATH
  5. Okan Bulut, Christopher David Desjardins: profileR: An R package for profile analysis (2020) not zbMATH
  6. Vinod, Hrishikesh D. (ed.); Rao, C. R. (ed.): Financial, macro and micro econometrics using R (2020)
  7. Arevalillo, Jorge M.; Navarro, Hilario: A stochastic ordering based on the canonical transformation of skew-normal vectors (2019)
  8. Dang, Yuanchu; Wang, Qing: Simultaneous variable and factor selection via sparse group Lasso in factor analysis (2019)
  9. David Navarro-Gonzalez; Andreu Vigil-Colet; Pere Ferrando; Urbano Lorenzo-Seva: Psychological Test Toolbox: A New Tool to Compute Factor Analysis Controlling Response Bias (2019) not zbMATH
  10. Rigdon, Edward E.; Becker, Jan-Michael; Sarstedt, Marko: Parceling cannot reduce factor indeterminacy in factor analysis: a research note (2019)
  11. Bellinger, Colin; Drummond, Christopher; Japkowicz, Nathalie: Manifold-based synthetic oversampling with manifold conformance estimation (2018)
  12. Klein, Hartmut; Hesse, Linnea; Boljen, Matthias; Kampowski, Tim; Butschek, Irina; Speck, Thomas; Speck, Olga: Finite element modelling of complex movements during self-sealing of ring incisions in leaves of \textitDelospermacooperi (2018)
  13. Mair, Patrick: Modern psychometrics with R (2018)
  14. Waller, Niels G.: Direct Schmid-Leiman transformations and rank-deficient loadings matrices (2018)
  15. Epskamp, Sacha; Rhemtulla, Mijke; Borsboom, Denny: Generalized network psychometrics: combining network and latent variable models (2017)
  16. Hessen, David J.: Lower bounds to the reliabilities of factor score estimators (2017)
  17. Tan, Teck Kiang: Doubly classified model with R (2017)
  18. Cantaluppi, Gabriele; Boari, Giuseppe: A partial least squares algorithm handling ordinal variables (2016)
  19. Johnson, Kent: Realism and uncertainty of unobservable common causes in factor analysis (2016)
  20. Najafabadi, Amir T. Payandeh; Najafabadi, Maryam Omidi: On the Bayesian estimation for Cronbach’s alpha (2016)

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