Comparar métodos

	Análise Fatorial Exploratória para Desenvolvimento de Escalas (AFE)	Alfa de Cronbach (Análise de Confiabilidade)	Análise de Componentes Principais
Área	Psicometria	Estatística	Aprendizado de máquina
Família	Latent structure	Latent structure	Machine learning
Ano de origem	1904 (foundational); contemporary scale-development practice from 1990s onward	1951	2002
Autor original	Primarily Spearman (1904); psychometric scale application formalised by Thurstone (1930s)	Lee J. Cronbach	Jolliffe, I.T. (textbook); Pearson & Hotelling (origins)
Tipo	Latent variable / dimension reduction	Reliability / internal consistency coefficient	Unsupervised dimensionality reduction
Fonte seminal	Costello, A. B. & Osborne, J. W. (2005). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Practical Assessment, Research & Evaluation, 10(7), 1–9.	Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334.	Jolliffe, I.T. (2002). Principal Component Analysis (2nd ed.). Springer.
Outros nomes	Açımlayıcı Faktör Analizi — Ölçek Geliştirme (EFA), psychometric EFA, scale construction factor analysis	coefficient alpha, alpha reliability, internal consistency reliability, Güvenilirlik Analizi (Cronbach Alpha)	Temel Bileşenler Analizi (PCA), PCA, principal components analysis, Karhunen-Loève transform
Relacionados	5	4	3
Resumo	Exploratory Factor Analysis for Scale Development is the psychometric application of EFA in which an item pool is administered and the resulting response data are analysed to discover the latent factor structure underlying the items. Originating with Spearman's (1904) factor theory and formalised for applied scale construction by Costello and Osborne (2005) and Fabrigar and colleagues (1999), this variant imposes a stricter sample requirement (n ≥ 100, subject-to-item ratio ≥ 5) and a higher loading threshold (≥ 0.40) than general EFA, and it treats the recovered factor structure as a draft to be subsequently validated by confirmatory analysis.	Cronbach's alpha is a coefficient of internal consistency that quantifies the degree to which a set of items on a scale measures the same underlying construct. Introduced by Lee J. Cronbach in 1951, it remains the most widely reported reliability index in social-science, health, and educational research.	Principal Component Analysis (PCA) is an unsupervised dimensionality-reduction method — given its modern textbook treatment by Ian Jolliffe (2002) — that compresses high-dimensional data into fewer dimensions while preserving the maximum possible variance. It re-expresses correlated variables as a small set of uncorrelated principal components ordered by how much of the data's variation each one captures.