Exploratory Factor Analysis and Principal Components Analysis

2011 ◽  
Vol 4 (2) ◽  
pp. 242 ◽  
Author(s):  
Mohammad Salehi

To investigate the construct validly of a section of a high stakes test, an exploratory factor analysis using principal components analysis was employed. The rotation used was varimax with the suppression level of .30. Eleven factors were extracted out of 35 reading comprehension items. The fact that these factors emerged speak to the construct validity of the test. However the problem of over-factoring was obvious. This may be attributable to different paradigms of testing on which the items were based. In other words, the test constructer opted for passages from TOEFL, FCE and IELTS books with much alteration.


2007 ◽  
Vol 100 (2) ◽  
pp. 355-364 ◽  
Author(s):  
Sook-Jeong Lee

The purpose of this study was to examine the psychometric properties of the Specific Interpersonal Trust scale of Johnson-George and Swap in Korean samples as a part of the process of providing an exemplary tool for intercultural studies of trust. A translated version of the original scale was administered to 337 university students (157 males, 180 females) in Seoul, Korea. Data were subjected to a principal components analysis and a confirmatory factor analysis. In principal components analysis for the Korean sample ( n = 167), three factors were identified and labeled: Overall Trust (Cronbach α=.89), Emotional Trust (Cronbach α = .88), and Reliableness (Cronbach α=.84). A confirmatory factor analysis ( n=170) showed that the three-factor model was valid for the sample (χ2/ df= 1.78, RMR=.06, RMSEA = .07, TLI=.92, CFI=.93). Internal consistency reliability and factorial validity were satisfactory in the case of the Korean sample. The Korean version of the Specific Interpersonal Trust Scale made good use of three factors of trust and appeared to be valid without sex differences, while the original scale distinguished the Males subscale from the Females subscale. Implications and limitations of this study were discussed.


2021 ◽  
Vol 13 (37) ◽  
pp. 4188-4219
Author(s):  
Peter D. Wentzell ◽  
Cannon Giglio ◽  
Mohsen Kompany-Zareh

Principal components analysis (PCA) is widely used in analytical chemistry, but is only one type of broader range of factor analysis tools that are described in this article.


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