Factor Structure of the My Education Scale

1988 ◽  
Vol 66 (3) ◽  
pp. 829-830
Author(s):  
William F. White ◽  
Michael Cass
Keyword(s):  
Factor Analysis ◽  
Factor Structure ◽  
Home Environment ◽  
Principal Components ◽  
Multiple Choice ◽  
Multiple Choice Questionnaire ◽  
Environment Index

Principal components factor analysis of responses of 442 students in Grades 6 and 7 yielded no clear evidence for a “home environment index” on the My Education scale, a 50-item multiple-choice questionnaire. To be a useful measure of motivation this scale needs further psychometric development.

Factor Analysis of the Stability of Self Scale

1980 ◽  
Vol 47 (3_suppl) ◽  
pp. 1160-1162 ◽  
Author(s):  
Stephen L. Franzoi ◽  
Benjamin J. Reddish
Keyword(s):  
Factor Analysis ◽  
Factor Structure ◽  
Principal Components ◽  
Analysis Data ◽  
Factor Solution ◽  
The Stability

The factor structure of Rosenberg's Stability of Self Scale (1965) was investigated via principal components factor analysis. Data from 92 male and 171 female undergraduates yielded a one-factor solution, supporting Rosenberg's contention that the scale is unidimensional.

Factor Analysis of a Multiple-Choice Format for Job Satisfaction

1987 ◽  
Vol 61 (3) ◽  
pp. 747-750 ◽  
Author(s):  
Terry Gregson
Keyword(s):  
Job Satisfaction ◽  
Factor Analysis ◽  
Factor Structure ◽  
Analytic Solution ◽  
Multiple Choice ◽  
Job Descriptive Index ◽  
Factor Analytic

This study examined the factor structure of a modified 30-question multiple-choice format for job satisfaction based on the Job Descriptive Index. The five-factor varimax factor analytic solution was the same as that obtained by Smith, Kendall, and Hulin (1969) for the original Job Descriptive Index. The measure of reliability was high. The results indicated that researchers can use a shorter multiple-choice format of job satisfaction based on the Job Descriptive Index without interfering with the dimensionality.

Factor Structure, Reliability, and Validity of the Death Attitude Profile-Revised

2000 ◽  
Vol 40 (3) ◽  
pp. 453-463 ◽  
Author(s):  
Richard Clements ◽  
Linda A. Rooda
Keyword(s):  
Factor Analysis ◽  
Factor Structure ◽  
Internal Consistency ◽  
Principal Components ◽  
Concurrent Validity ◽  
Reliability And Validity ◽  
Fear Of Death ◽  
Hospice Nurses ◽  
Structure Reliability ◽  
Two Factors

The Present Study Examined The Factor Structure, reliability, and validity of the Death Attitude Profile-Revised (DAP-R; Wong, Reker, & Gesser, 1994) using a sample of 403 hospital and hospice nurses. A principal-components factor analysis of the DAP-R indicated that the DAP-R may consist of six factors instead of the five originally reported by Wong et al. The first four factors reported by Wong et al., which correspond to the subscales that they labeled Fear of Death, Death Avoidance, Approach Acceptance, and Escape Acceptance, were replicated in the present study, and these subscales were found to have acceptable levels of internal consistency and to possess some degree of concurrent validity. However, the items which loaded on the fifth factor in Wong et al.‘s study (their “Neutral Acceptance” subscale) were split across two factors in the present study, suggesting that this subscale may not be measuring a unitary construct.

A Factor Analysis of Raven's Advanced Progressive Matrices Freed of Difficulty Factors

1981 ◽  
Vol 41 (4) ◽  
pp. 1295-1302 ◽  
Author(s):  
Ronna F. Dillon ◽  
John T. Pohlmann ◽  
David F. Lohman
Keyword(s):  
Factor Analysis ◽  
Factor Structure ◽  
Principal Components ◽  
Item Difficulty ◽  
Guttman Scale ◽  
Successful Performance ◽  
Logical Operations ◽  
Factor Ii ◽  
Components Analysis ◽  
Raven's Advanced Progressive Matrices

The study presents a factor analysis of the 1962 revision of the Advanced Progressive Matrices (APM). The analysis was conducted such that substantive factor structure interpretations were freed of the effects of differences in item difficulty. The APM test was given to 237 examinees, 16–18 years old. The data were subjected to a Guttman scale analysis to determine whether the APM could be interpreted as a one factor instrument. Then the phi/phi max inter-item correlation matrix was factored. A principal components analysis, followed by a series of varimax rotations of the principal components, was performed. The Guttman coefficients of scalability were too small to support a one factor theory of the APM. The 2-factor solution provided the most interpretable factor structure. Factor I was composed of items in which the solution was obtained by adding or subtracting patterns. Factor II was composed of items in which the solution was based on the ability to perceive the progression of a pattern. Results are discussed in terms of representative cognitive tests and tasks believed to embody the logical operations responsible for successful performance on items loading on each factor. The possibility of forming subtests of items to enhance the predictive validity of the matrices also is discussed.

Factor Analysis of the General Health Questionnaire

1994 ◽  
Vol 75 (2) ◽  
pp. 979-983 ◽  
Author(s):  
Richard S. Epstein ◽  
Carol S. Fullerton ◽  
Robert J. Ursano
Keyword(s):  
Factor Analysis ◽  
Principal Components Analysis ◽  
Factor Structure ◽  
Principal Components ◽  
General Health ◽  
Depressive Symptomatology ◽  
General Health Questionnaire ◽  
Health Questionnaire ◽  
Components Analysis ◽  
Army Soldiers

We present the factor structure of the General Health Questionnaire-60 as derived from a population of 2115 Army soldiers. An eight-factor principal components analysis provided the most clinically relevant solution and explained 58.0% of the variance. We distinguished two types of depressive symptomatology, suggesting the questionnaire may be useful in differentiating shame-ridden dysphoria from anergic disinterest.

Factor Structure of The Beck Depression Inventory in a University Sample

2003 ◽  
Vol 92 (1) ◽  
pp. 53-61 ◽  
Author(s):  
Herbert W. Helm ◽  
Mark D. Boward
Keyword(s):  
College Students ◽  
Factor Analysis ◽  
Beck Depression Inventory ◽  
Factor Structure ◽  
Principal Components ◽  
Varimax Rotation ◽  
Common Variance ◽  
Factor Solution ◽  
The Common ◽  
Components Analysis

Factor analysis was performed on the Beck Depression Inventory with a university sample to examine its potential multidimensionality. A principal components analysis with an oblimin and varimax rotation produced a two-factor solution. These factors were labeled Cognitive–Affective and Physiological and accounted for approximately 39% of the common variance. This finding is consistent with multidimensionality of the inventory and with a similar study of college students. The commonalities of the two studies suggest the reliability (internal consistency) of the Cognitive-Affective and Physiological constructs among “minimally” depressed university samples.

scholarly journals On the Factor Structure of a Reading Comprehension Test

2011 ◽  
Vol 4 (2) ◽  
pp. 242 ◽  
Author(s):  
Mohammad Salehi
Keyword(s):  
Factor Analysis ◽  
Reading Comprehension ◽  
Construct Validity ◽  
Principal Components Analysis ◽  
Exploratory Factor Analysis ◽  
Factor Structure ◽  
Principal Components ◽  
High Stakes ◽  
Comprehension Test ◽  
Components Analysis

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.

Factor Analysis and Rotation of Responses to the Junior Eysenck Personality Inventory

1977 ◽  
Vol 40 (2) ◽  
pp. 599-601 ◽  
Author(s):  
Robert A. C. Stewart
Keyword(s):  
Factor Analysis ◽  
New Zealand ◽  
Principal Components Analysis ◽  
Factor Structure ◽  
Principal Components ◽  
Personality Inventory ◽  
Varimax Rotation ◽  
Eysenck Personality Inventory ◽  
Components Analysis ◽  
Affect Factor

To investigate further the basic item-factor structure of the Junior Eysenck Personality Inventory, a principal components analysis and varimax rotation were conducted on responses of 866 children (aged 7 to 16 yr.) from schools in the Rotorua area of New Zealand. Ten factors were extracted of which 7 were interpretable. These were named: Factor 1. Neuroticism I (Neurotic affect), Factor 2. Extraversion I (Impulsivity), Factor 3. Lie Scale, Factor 4. Extraversion II (Introversion), Factor 5. Extraversion III (Jocularity), Factor 6. Extraversion IV (Sociability), Factor 8. Neuroticism II (Neurotic ideation).

Factor Structure of a Clients' Satisfaction Scale with Psychiatric Inpatients

1983 ◽  
Vol 53 (3_suppl) ◽  
pp. 1155-1159 ◽  
Author(s):  
M. K. Distefano ◽  
Margaret W. Pryer ◽  
Betty F. Baker
Keyword(s):  
Factor Analysis ◽  
Factor Structure ◽  
Principal Components ◽  
Psychiatric Inpatients ◽  
Total Variance ◽  
Satisfaction Scale ◽  
Satisfaction Questionnaire ◽  
General Satisfaction

A principal-components factor analysis of the responses of 119 psychiatric inpatients to a 28-item clients satisfaction questionnaire yielded two interpretable factors that accounted for 52% of the total variance. The first factor concerned general satisfaction with the treatment and staff and the second factor focused on satisfaction with the activities and environment. The results of other factor studies were reported, and the methodological influences on the dimensionality of satisfaction were discussed.

The Development of the Job Stressor Appraisal Scale as Part of the Job Stress Battery

2012 ◽  
Vol 28 (2) ◽  
pp. 147-153 ◽  
Author(s):  
Ilknur Özalp Türetgen ◽  
Özlem Sertel Berk ◽  
Gokce Basbug ◽  
Pinar Unsal
Keyword(s):  
Factor Analysis ◽  
Job Stress ◽  
Factor Structure ◽  
Validity And Reliability ◽  
Job Stressors ◽  
Job Stressor

This study introduces the psychometric qualities of the Job Stressor Appraisal Scale (JSAS), a part of the Job Stress Battery, which comprehensively measures job stress in terms of job stressors, moderators, and strains. The JSAS measures employees’ appraisals of job stressors by considering both their frequency and intensity. To test its psychometric qualities, we administered the JSAS to a sample of 1,069 employees in Turkey. Factor analysis revealed a 5-factor structure, with 43 items explaining 46.1% of the variance. Cronbach’s α coefficients of the factors and the total scale varied between .66 and .93. In terms of construct and convergent validities, results generally showed significant correlations in the expected directions. These findings obtained on the validity and reliability of the scale imply good psychometric qualities.

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