临床研究中的探索性因子分析与主成分分析:您应选用哪一种? | Zendy

Alavi Mousa | Zendy; Visentin Denis C. | Zendy; Thapa Deependra K. | Zendy; Hunt Glenn E. | Zendy; Watson Roger | Zendy; Cleary Michelle | Zendy

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临床研究中的探索性因子分析与主成分分析:您应选用哪一种?

Author(s) -

Alavi Mousa,

Visentin Denis C.,

Thapa Deependra K.,

Hunt Glenn E.,

Watson Roger,

Cleary Michelle

Publication year - 2020

Publication title -

journal of advanced nursing

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.948

H-Index - 155

eISSN - 1365-2648

pISSN - 0309-2402

DOI - 10.1111/jan.14377

Subject(s) - principal component analysis , exploratory factor analysis , exploratory analysis , component (thermodynamics) , factor (programming language) , component analysis , psychology , computer science , statistics , data science , clinical psychology , mathematics , psychometrics , physics , thermodynamics , programming language

Factor analysis covers a range of multivariate methods used to explain how underlying factors influence a set of observed variables. When research aims to identify these underlying factors, exploratory factor analysis (EFA) is used. In contrast, when the aim is to test whether a set of observed variables influences responses in accordance with an existing conceptual basis, confirmatory factor analysis is performed. EFA has many similarities with a commonly used data reduction technique called principal component analysis (PCA).

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