Robustness of autoencoders for establishing psychometric properties based on small sample sizes: res...
Robustness of autoencoders for establishing psychometric properties based on small sample sizes: results from a Monte Carlo simulation study and a sports fan curiosity study
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United States: PeerJ. Ltd
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English
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United States: PeerJ. Ltd
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The principal component analysis (PCA) is known as a multivariate statistical model for reducing dimensions into a representation of principal components. Thus, the PCA is commonly adopted for establishing psychometric properties,
the construct validity. Autoencoder is a neural network model, which has also been shown to perform well in dimensio...
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Robustness of autoencoders for establishing psychometric properties based on small sample sizes: results from a Monte Carlo simulation study and a sports fan curiosity study
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TN_cdi_doaj_primary_oai_doaj_org_article_fe716bdc10dd4e949ab386a84c6f534e
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_fe716bdc10dd4e949ab386a84c6f534e
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2376-5992
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2376-5992
DOI
10.7717/peerj-cs.782
