Factor recovery by principal axis factoring and maximum likelihood factor analysis as a function of factor pattern and sample size

2012 ◽  
Vol 39 (4) ◽  
pp. 695-710 ◽  
Author(s):  
J. C.F. de Winter ◽  
D. Dodou
Keyword(s):  
Factor Analysis ◽  
Maximum Likelihood ◽  
Sample Size ◽  
Principal Axis ◽  
Maximum Likelihood Factor Analysis ◽  
Factor Pattern ◽  
Principal Axis Factoring

Validity of Higher-Order Ability Constructs in Structure-of-Intellect Tests All Involving Semantic Content and Operations of Cognition or Evaluation: A Confirmatory Maximum Likelihood Factor Analysis

1985 ◽  
Vol 45 (2) ◽  
pp. 353-359 ◽  
Author(s):  
David E. Mace ◽  
William B. Michael ◽  
Dennis Hocevar
Keyword(s):  
Factor Analysis ◽  
Maximum Likelihood ◽  
Semantic Content ◽  
Higher Order ◽  
Second Order ◽  
Third Order ◽  
Maximum Likelihood Factor Analysis ◽  
Practical Standpoint ◽  
Order Factor ◽  
Structure Of Intellect

Through use of confirmatory maximum likelihood factor analysis in conjunction with the LISREL V computer program devised by Jöreskog and Sörbom, an evaluation was made of the validity of higher-order ability constructs in structure-of-intellect tests all containing semantic content and operations of cognition or evaluation. The hypothesized first-, second-, and third-order factors were all reproducible with every one of the estimated factor loadings being significant beyond the .01 level. Although the first- and second-order factors were shown to be reproducible and statistically separable, the high intercorrelations among the six first-order product factors and the two second-order operations factors would suggest from a practical standpoint that the single third-order factor of semantic content would constitute a plausible alternative for accounting for much of the covariance among the test variables.

scholarly journals VALUES OF YOUNG EMPLOYEES: Z-GENERATION PERCEPTION

2020 ◽  
Vol 21 (1) ◽  
pp. 10-17
Author(s):  
Jelena Titko ◽  
Anna Svirina ◽  
Viktorija Skvarciany ◽  
Inga Shina
Keyword(s):  
Professional Development ◽  
Factor Analysis ◽  
Personality Trait ◽  
Correlation Matrix ◽  
Principal Axis ◽  
Image Correlation ◽  
Processing Factor ◽  
Number Of Factors ◽  
Bartlett’S Test ◽  
Principal Axis Factoring

The current paper aims to analyse the importance of values of young employees now and in five years period. In order to achieve the aim, the questionnaire consisting of fifty statements was developed and disseminated between the Latvian students. The sample size was 392, which shows that the results represent the whole populations. For data processing, factor analysis was chosen as a tool. The data factorability was assessed via Bartlett’s Test of Sphericity, Kaiser-Myer-Olkin (KMO) statistic, initial estimates of communality and the anti-image correlation matrix. The factors were extracted via principal axis factoring (PAF). The number of factors was determined by the scree plot/Kaiser’s rule and was equal to five in both cases. The results showed the for the young employees the essential values today are those connected to the personality trait. However, in five years, the essential values would be those that are linked to professional development.

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