Construction of the average variance extracted index for construct validation in structural equation models with adaptive regressions

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.creatorSantos, Patricia Mendes dos-
Autor(es): dc.creatorCirillo, Marcelo Ângelo-
Data de aceite: dc.date.accessioned2026-02-09T12:31:32Z-
Data de disponibilização: dc.date.available2026-02-09T12:31:32Z-
Data de envio: dc.date.issued2022-02-14-
Data de envio: dc.date.issued2022-02-14-
Data de envio: dc.date.issued2020-
Fonte completa do material: dc.identifierhttps://repositorio.ufla.br/handle/1/49332-
Fonte completa do material: dc.identifierhttps://doi.org/10.1080/03610918.2021.1888122-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1163039-
Descrição: dc.descriptionA range of indicators, such as the average variance extracted (AVE), is commonly used to validate constructs. In statistics, AVE is a measure of the amount of variance that is captured by a construct in relation to the amount of variance due to measurement error. These conventional indices are formed by factor loadings resulting from estimated least squares or maximum likelihood regressions. Thus, a new proposition that provides new factor loadings may result in a more informative AVE index. Consequently, this study consists of the improvement of the index by using adaptive regressions. A Monte Carlo simulation study was performed considering different numbers of outliers generated by distributions with symmetry deviations and excess kurtosis and sample sizes defined as n = 50, 100, and 200. The conclusion was that, in formative structural models, the adaptive linear regression (ALR) method showed good efficiency for correctly specified models. The results obtained from the ALR method for models with specification errors showed low efficiency, as expected.-
Idioma: dc.languageen-
Publicador: dc.publisherTaylor & Francis-
Direitos: dc.rightsrestrictAccess-
???dc.source???: dc.sourceCommunications in Statistics - Simulation and Computation-
Palavras-chave: dc.subjectAdaptive regression-
Palavras-chave: dc.subjectStructural equation model-
Palavras-chave: dc.subjectOutliers-
Palavras-chave: dc.subjectAverage variance extracted-
Palavras-chave: dc.subjectMonte Carlo simulation-
Palavras-chave: dc.subjectRegressão adaptativa-
Palavras-chave: dc.subjectModelo de equação estrutural-
Palavras-chave: dc.subjectVariação média extraída-
Palavras-chave: dc.subjectSimulação de Monte Carlo-
Título: dc.titleConstruction of the average variance extracted index for construct validation in structural equation models with adaptive regressions-
Tipo de arquivo: dc.typeArtigo-
Aparece nas coleções:Repositório Institucional da Universidade Federal de Lavras (RIUFLA)

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