Estimating the dimensionality of intelligence like data using Exploratory Graph Analysis
By Hudson F. Golino, Andreas Demetriou. 2017
121 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Experimental and Cognitive Psychology
View Paper: https://www.semanticscholar.org/paper/daa91e1bbee16ab6c1e0c2bd55a049b775e60701
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
In Experimental and Cognitive Psychology
- Alexander P. Christensen
- Paul J Silvia
- L. E. Garrido
- M. D. Nieto
- Agustín Martínez-Molina
- Dingjing Shi
- R. Sadana
- Hudson F. Golino
Citations in the corpus
- Investigating the performance of Exploratory Graph analysis and traditional techniques to identify the number of latent factors: a simulation and tutorial (2018, result): “Also, while preliminary studies have compared traditional factor analytic methods with EGA (Golino & Demetriou, 2017; Golino & Epskamp, 2017), there is a need to compare the performance of EGA with different types of parallel analysis as well as techniques based on the scree test (Cattell, 1966),…”
- A Psychometric Network Perspective on the Validity and Validation of Personality Trait Questionnaires (2019, methodology): “…simulation studies have shown that EGA has comparable or better accuracy for identifying the number of dimensions than the most accurate factor analytic techniques (e.g. parallel analysis; Christensen, 2020; Golino and Demetriou, 2017; Golino and Epskamp, 2017; Golino et al., 2020).”