Enhancement of physiological factors in factor analysis of dynamic studies

1986 ◽  
Vol 12 (5-6) ◽  
pp. 280-283 ◽  
Author(s):  
Martin Šámal ◽  
Helena Sůrová ◽  
Miroslav Kárný ◽  
Eva Maříková ◽  
Kateřina Michalová ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Physiological Factors ◽  
Dynamic Studies

scholarly journals ANALISIS FAKTOR YANG MEMPENGARUHI PRESTASI BELAJAR MATA PELAJARAN DI SMP NEGERI 03 KEPANJEN

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Kardisius Agot ◽  
Rusno Rusno ◽  
Walipah Walipah
Keyword(s):  
Factor Analysis ◽  
Environmental Factors ◽  
Social Studies ◽  
Family Environment ◽  
School Environment ◽  
Physiological Factors ◽  
Learning Achievement ◽  
Data Collection Technique ◽  
Learning Interest ◽  
Method Factors

The purpose of this study is 1. to find out and analyze what factors influence the success of social studies learning achievement in students of SMP Negeri 03 Kepanjen Malang Regency.2. To find out and analyze the dominant factors that influence the learning achievement of social studies subjects in SMP Negeri 03 Kepanjen. The population in this study were students of class VII in SMP Negeri 03 Kepanjen whose IPS scores were less than KKM, totaling 186 students. And the sample is 48 students. The data collection technique used was Questionnaire Data obtained were analyzed by factor analysis techniques. This type of research uses factor analysis using Bartlett's lest of Sphericity. Based on the results of the study showed that there were 15 (fifteen) learning achievement factors formed, these factors were as follows: (1) family environmental factors, 17.21% (2) 7.80% material mastery factors. (3) class atmosphere factors, 6.80%. (4) learning source factors are 5.95%. (5) student activeness factor is 4.68%. (6) learning interest factors are 4.48%. (7) school environment factors, 3.92%. (8) physiological factors of students, 3.68%. (9) learning method factors 3.39%. (10) community environmental factors 3.21%. (11) the teacher discipline factor is 2.99%. (12) the method of teaching methods of teachers is 2.85%. (13) student readiness factor 2.68%. (14) learning facility factors 2.56% (15) curriculum factors 2.35%. The factor which gave the biggest contribution was the family environment factor, which was 17.21%. The smallest contribution is given by the curriculum factor which is 2.35%.

On the existence of an unambiguous solution in factor analysis of dynamic studies

1989 ◽  
Vol 34 (2) ◽  
pp. 223-228 ◽  
Author(s):  
M Samal ◽  
M Karny ◽  
H Surova ◽  
P Penicka ◽  
E Marikova ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Dynamic Studies

Factor Analysis of Measures of Articulation, Language, Auditory Processing, Reading-Spelling, and Maxillofacial Structure

1977 ◽  
Vol 20 (2) ◽  
pp. 319-324
Author(s):  
Anita F. Johnson ◽  
Ralph L. Shelton ◽  
William B. Arndt ◽  
Montie L. Furr
Keyword(s):  
Factor Analysis ◽  
Clinical Judgment ◽  
Auditory Processing

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.

Evidence-based subtypes in functional dyspepsia with confirmatory factor analysis: Psychosocial and physiopathological correlates

2001 ◽  
Vol 120 (5) ◽  
pp. A51-A52 ◽  
Author(s):  
B FISCHLER ◽  
J VANDENBERGHE ◽  
P PERSOONS ◽  
V GUCHT ◽  
D BROEKAERT ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Functional Dyspepsia ◽  
Evidence Based ◽  
Confirmatory Factor

The French Version of the Revised Child Anxiety and Depression Scale (RCADS) in a Nonclinical Sample

2015 ◽  
Vol 74 (3) ◽  
pp. 119-127 ◽  
Author(s):  
Martine Bouvard ◽  
Anne Denis ◽  
Jean-Luc Roulin
Keyword(s):  
Factor Analysis ◽  
Anxiety Disorder ◽  
Confirmatory Factor Analysis ◽  
Generalized Anxiety Disorder ◽  
Child Anxiety ◽  
Depression Scale ◽  
Anxiety And Depression ◽  
Generalized Anxiety ◽  
French Version ◽  
Confirmatory Factor

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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