Family Strengths and the Kansas Marital Satisfaction Scale: A Factor Analytic Study

2001 ◽  
Vol 88 (3_suppl) ◽  
pp. 965-973 ◽  
Author(s):  
Walter R. Schumm ◽  
Stephan R. Bollman ◽  
Anthony P. Jurich ◽  
Ruth C. Hatch
Keyword(s):  
Factor Analysis ◽  
Marital Satisfaction ◽  
Construct Validity ◽  
Common Factor ◽  
Disciples Of Christ ◽  
Family Strengths ◽  
Christian Church ◽  
Satisfaction Scale ◽  
Factor Analytic ◽  
Factor Analytic Study

20 new items were developed to measure six concepts of family strengths and were administered, along with the Kansas Marital Satisfaction Scale, to over 266 married subjects as part of a larger survey of current and former members of the Christian Church (Disciples of Christ). A common factor analysis suggested that most of the items were associated with their expected factors, while reliability analyses indicated that most of the scales had acceptable estimates of internal consistency. The marital satisfaction items clearly were associated with their own factor and not other factors, providing support for the unidimensional nature of the Kansas Marital Satisfaction Scale and for its construct validity.

Dimensionality of the Marital Communication Inventory: A Preliminary Factor Analytic Study

1979 ◽  
Vol 45 (1) ◽  
pp. 123-128 ◽  
Author(s):  
Walter R. Schumm ◽  
Charles R. Figley ◽  
Anthony P. Jurich
Keyword(s):  
Factor Analysis ◽  
Marital Adjustment ◽  
Common Factor ◽  
Married Couples ◽  
Analytic Study ◽  
Marital Communication ◽  
Varimax Rotation ◽  
Future Assessment ◽  
Factor Analytic ◽  
Factor Analytic Study

An abbreviated version of the Marital Communication Inventory was administered to a university sample of 54 married couples in an earlier study. To assess the dimensionality of the scale, the data were analyzed through a common factor analysis with varimax rotation. Results indicate that the inventory does not appear to be unidimensional as has been commonly assumed, but instead appears to be heavily loaded with an element of marital adjustment or conventionality rather than being solely a measure of marital communication. The consequences for previous research and the implications for the future assessment of marital communication by researchers and clinicians are discussed. Guidelines for further investigation of the validity of the inventory are proposed.

Factor Analytic Study of the Test, what Kind of Person are You?

1974 ◽  
Vol 39 (1) ◽  
pp. 143-146 ◽  
Author(s):  
Joseph C. Bledsoe ◽  
Joe Khatena
Keyword(s):  
Factor Analysis ◽  
Construct Validity ◽  
Analytic Study ◽  
Self Perception ◽  
Self Perceptions ◽  
Self Confidence ◽  
Factor Analytic ◽  
Factor Analytic Study ◽  
Five Factors

A factor analysis of 645 responses to What Kind of Person Are You? test, a 50-item inventory of self-perception of creativity, yielded five factors: Acceptance of Authority, Self-confidence, Inquisitiveness, Awareness of Others and Disciplined Imagination. The analysis gives some support to the construct validity of the measure, providing a more sensitive appraisal of an individual's self-perceptions including creative and less creative orientations.

Factor Analytic Study of Something about Myself

1973 ◽  
Vol 32 (3_suppl) ◽  
pp. 1176-1178 ◽  
Author(s):  
Joseph C. Bledsoe ◽  
Joe Khatena
Keyword(s):  
Factor Analysis ◽  
Construct Validity ◽  
Analytic Study ◽  
Environmental Sensitivity ◽  
Factor Analytic ◽  
Factor Analytic Study ◽  
Creative Individual ◽  
Self Reports

A factor analysis of 662 responses to Something About Myself, a 50-item inventory of self-reports of creativity, yielded six orthogonal factors: Environmental sensitivity, Initiative, Self-strength, Intellectuality, Individuality, and Artistry. The analysis further supports the construct validity of the measure and provides a means for more sensitive appraisal of the creative individual and comparisons among various subgroups.

Gender and Marital Satisfaction: A Replication with a Sample of Spouses from the Christian Church (Disciples of Christ)

1996 ◽  
Vol 79 (2) ◽  
pp. 496-498 ◽  
Author(s):  
Walter R. Schumm ◽  
Benjamin Silliman
Keyword(s):  
Marital Satisfaction ◽  
Effect Size ◽  
Gender Effect ◽  
Disciples Of Christ ◽  
Church Members ◽  
Christian Church ◽  
Satisfaction Scale

In a subsample of 57 husbands and 120 wives who had participated in a larger study of retention of church members, an effect size of 0.23 was found between gender and marital satisfaction as measured by the Kansas Marital Satisfaction Scale. The results are consistent with previous findings of a gender effect, the “his and hers” marriage.

Factor-Analytic Study of the Maitland Graves Design Judgment Test

1967 ◽  
Vol 24 (1) ◽  
pp. 73-74 ◽  
Author(s):  
H. J. Eysenck
Keyword(s):  
Factor Analysis ◽  
Analytic Study ◽  
Young Males ◽  
Factor Analytic ◽  
Factor Analytic Study ◽  
Five Factors

A factor-analysis was carried out of the 90 items of the Maitland Graves Design Judgment Test based on responses from 172 young males. Five factors were found, of which only four could be interpreted.

Dimensional Analyses of Taxonic Data

2007 ◽  
Vol 101 (2) ◽  
pp. 617-635 ◽  
Author(s):  
William M. Grove
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Data Structures ◽  
Principal Components ◽  
Common Factor ◽  
Principal Component ◽  
Mixed Population ◽  
Single Population ◽  
Factor Analytic ◽  
Mixed Populations

Principal component analysis (PCA) and common factor analysis are often used to model latent data structures. Typically, such analyses assume a single population whose correlation or covariance matrix is modelled. However, data may sometimes be unwittingly sampled from mixed populations containing a taxon (nonarbitrary subpopulation) and its complement class. One derives relations between values of PCA parameters within subpopulations and their values in the mixed population. These results are then extended to factor analysis in mixed populations. As relationships between subpopulation and mixed-population principal components and factors sensitively depend on within-subpopulation structures and between-subpopulation differences, naive interpretation of PCA or factor analytic findings can potentially mislead. Several analyses, better suited to the dimensional analysis of admixture data structures, are presented and compared.

Sign in / Sign up

Export Citation Format

Share Document