Investigations on Non-Gaussian Factor Analysis

2004 ◽  
Vol 11 (7) ◽  
pp. 597-600 ◽  
Author(s):  
Z.-Y. Liu ◽  
K.-C. Chiu ◽  
L. Xu
Keyword(s):  
2019 ◽  
Vol 89 (9) ◽  
pp. 1555-1573
Author(s):  
Maengseok Noh ◽  
Youngjo Lee ◽  
Johan H.L. Oud ◽  
Toni Toharudin

2004 ◽  
Vol 07 (03) ◽  
pp. 253-267 ◽  
Author(s):  
KAI-CHUN CHIU ◽  
LEI XU

In the context of quantitative analysis of the arbitrage pricing theory (APT) model, conventional factor analytic approaches such as maximum likelihood factor analysis (MLFA) cannot provide satisfactory answers to two important questions. The first one concerns the correct identification of factor number while the second one is related to the rotation indeterminacy of factor loadings. In the literature, MLFA followed by likelihood ratio (LR) test and the analysis of eigenvalues of sample covariance matrix were two popular approaches used to determine the appropriate number of factors. However, it was shown empirically that both of them suffered from different kinds of biases. We find the recently developed non-gaussian factor analysis (NFA) model by Xu [24] provides a new perspective for the determination of the appropriate factor number k in APT, with promising empirical results demonstrated.


1977 ◽  
Vol 20 (2) ◽  
pp. 319-324
Author(s):  
Anita F. Johnson ◽  
Ralph L. Shelton ◽  
William B. Arndt ◽  
Montie L. Furr

This study was concerned with the correspondence between the classification of measures by clinical judgment and by factor analysis. Forty-six measures were selected to assess language, auditory processing, reading-spelling, maxillofacial structure, articulation, and other processes. These were applied to 98 misarticulating eight- and nine-year-old children. Factors derived from the analysis corresponded well with categories the measures were selected to represent.


2001 ◽  
Vol 120 (5) ◽  
pp. A51-A52 ◽  
Author(s):  
B FISCHLER ◽  
J VANDENBERGHE ◽  
P PERSOONS ◽  
V GUCHT ◽  
D BROEKAERT ◽  
...  

2015 ◽  
Vol 74 (3) ◽  
pp. 119-127 ◽  
Author(s):  
Martine Bouvard ◽  
Anne Denis ◽  
Jean-Luc Roulin

This article investigates the psychometric properties of the Revised Child Anxiety and Depression Scale (RCADS). A group of 704 adolescents completed the questionnaires in their classrooms. This study examines potential confirmatory factor analysis factor models of the RCADS as well as the relationships between the RCADS and the Screen for Child Anxiety Related Emotional Disorders-Revised (SCARED-R). A subsample of 595 adolescents also completed an anxiety questionnaire (Fear Survey Schedule for Children-Revised, FSSC-R) and a depression questionnaire (Center for Epidemiological Studies Depression Scale, CES-D). Confirmatory factor analysis of the RCADS suggests that the 6-factor model reasonably fits the data. All subscales were positively intercorrelated, with rs varying between .48 (generalized anxiety disorder-major depression disorder) and .65 (generalized anxiety disorder-social phobia/obsessive-compulsive disorder). The RCADS total score and all the RCADS scales were found to have good internal consistency (> .70). The correlations between the RCADS subscales and their SCARED-R counterparts are generally substantial. Convergent validity was found with the FSSC-R and the CES-D. The study included normal adolescents aged 10 to 19. Therefore, the findings cannot be extended to children under 10, nor to a clinical population. Altogether, the French version of the RCADS showed reasonable psychometric properties.


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