2017
DOI: 10.6018/analesps.33.2.270211
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El análisis factorial exploratorio de los ítems: análisis guiado según los datos empíricos y el software.

Abstract: <span style="font-family: 'Garamond',serif; font-size: 8pt; mso-bidi-font-size: 10.0pt; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: AR-SA; mso-bidi-language: AR-SA;" lang="EN-US">The aim of the present study is to illustrate how the appropriate or inappropriate application of exploratory factor analysis (EFA) can lead to quite different conclusions. To reach this goal, we evaluated the degree to which four different … Show more

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Cited by 139 publications
(112 citation statements)
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“…We conducted a descriptive analysis for sample characteristics and items of the GPQ. With regard to validity analysis based on internal structure, we performed an Exploratory Factor Analysis (EFA) using the maximum likelihood (ML) method and oblique rotation following the recommended standards (Lloret et al, 2017). Previously, we analyzed whether our data fitted the conditions for linear factor analysis (Lloret et al, 2017) and we tested the floor and ceiling effects of each item (percentage of response above 95% in scores 1 and 6).…”
Section: Methodsmentioning
confidence: 99%
“…We conducted a descriptive analysis for sample characteristics and items of the GPQ. With regard to validity analysis based on internal structure, we performed an Exploratory Factor Analysis (EFA) using the maximum likelihood (ML) method and oblique rotation following the recommended standards (Lloret et al, 2017). Previously, we analyzed whether our data fitted the conditions for linear factor analysis (Lloret et al, 2017) and we tested the floor and ceiling effects of each item (percentage of response above 95% in scores 1 and 6).…”
Section: Methodsmentioning
confidence: 99%
“…Factorial validity was examined with all participants except for healthy controls ( n = 305) using principal components analysis (PCA) with an oblique “Promax” rotation to identify the number of components and determine the factor structure. PCA was conducted using polychoric correlations due to the ordinal nature of the data (22–24). The Kaiser-Meyer-Olkin measure of sampling adequacy was used to determine adequacy of sample size, and Bartlett's test of sphericity was used to assess suitability of the data for PCA.…”
Section: Methodsmentioning
confidence: 99%
“…En relación a la asimetría y curtosis, a excepción de algunos ítems, la mayoría se encuentra entre ± 2.00 (George & Mallery, 2016). Por último, se evidencia aceptables cargas factoriales (λ), los cuales fueron superior a 0.50 (Lloret, Ferreres, Hernández & Tomás, 2017 En cuanto al AFC de los modelos reportados por estudios psicométricos, se evidencia que todos los modelos (M1, M2, M3, M4 y M5) presentan adecuados índices de ajuste. Sin embargo, la correlación interfactorial del modelo de dos (ψ = 0.94), tres (ψpromedio = 0.94), cuatro (ψpromedio = 0.88) y cinco factores (ψpromedio = 0.77) fue alta, indicando la presencia de un factor general.…”
Section: Resultsunclassified