Psychometric Characteristics of the Minimum Data Set I: Confirmatory Factor Analysis

Studies on the concept of happiness have led to questions about whether all symptoms of happiness correspond to a real and healthy emotional state. Therefore, in this research, a scale was developed to examine the concept of “authentic happiness” coined by Seligman. Firstly, literature that explains authentic happiness and defines its relationship to other psychological concepts was reviewed, and then a theoretical framework was developed based on this information and the psychometric characteristics of the scale were introduced. The results of the confirmatory factor analysis revealed that the fit indices were compatible with twodimensional structure. These two dimensions have been entitled as “Authentic Happiness” and “Fluctuating Happiness”. Based on the findings of the present study, the Authentic Happiness Scale (AHS) is a reliable and valid scale to determine the authentic happiness levels of university students.

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Psychometric Characteristics of the Turkish Version of Adolescent Lifestyle Profile R2

Journal of Nursing Measurement ◽

10.1891/1061-3749.26.2.249 ◽

2018 ◽

Vol 26 (2) ◽

pp. 249-263

Author(s):

Nesrin İlhan ◽

Ayşe Yildiz

Keyword(s):

Factor Analysis ◽

Confirmatory Factor Analysis ◽

Life Style ◽

Goodness Of Fit ◽

Healthy Lifestyle ◽

Psychometric Testing ◽

Turkish Version ◽

Psychometric Characteristics ◽

Total Correlation ◽

Confirmatory Factor

Background and Purpose:The purpose of this study was to adapt and assess cultural and psychometric properties of the Adolescent Life Style Profile (ALP-R2) in Turkish adolescents.Methods:The sample of the study consisted of 945 students aged 12–18 years. Data were collected using the Turkish translation of the ALP-R2. Psychometric testing of the ALP-R2 included internal consistency, item-total correlation, test–retest correlation, and construct validity with confirmatory factor analysis (CFA).Results:The total Cronbach’s α coefficient was .88, and the subscales ranged from .55 to .76. The CFA results showed that the structure of the model/scale has an acceptable goodness of fit.Conclusion:The study shows that the Turkish version of the ALP-R2 is a reliable and valid scale that can be used to assess healthy lifestyle domains in Turkish adolescents.

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Testing Factorial Invariance across Groups: A Reconceptualization and Proposed New Method

Journal of Management ◽

10.1177/014920639902500101 ◽

1999 ◽

Vol 25 (1) ◽

pp. 1-27 ◽

Cited By ~ 318

Author(s):

Gordon W. Cheung ◽

Roger B. Rensvold

Keyword(s):

Factor Analysis ◽

Confirmatory Factor Analysis ◽

Latent Variables ◽

Cross Cultural ◽

Factorial Invariance ◽

Published Data ◽

Data Set ◽

Test Items ◽

Confirmatory Factor ◽

Different Cultures

Many cross-cultural researchers are concerned with factorial invariance; that is, with whether or not members of different cultures associate survey items, or similar measures, with similar constructs. Researchers usually test items for factorial invariance using confirmatory factor analysis (CFA). CFA, however, poses certain problems that must be dealt with. Primary among them is standardization, the process that assigns units of measurement to the constructs (latent variables). Two standardization procedures and several minor variants have been reported in the literature, but using these procedures when testing for factorial invariance can lead to inaccurate results. In this paper we review basic theory, and propose an extension of Byrne, Shavelson, and Muthgn’s (1989) procedure for identifying non-invariant items. The extended procedure solves the standardization problem by performing a systematic comparison of all pairs of factor loadings across groups. A numerical example based upon a large published data set is presented to illustrate the utility of the new procedure, particularly with regard to partial factorial invariance.

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Testing the Psychometric Characteristics of the Revised Mastery of Stress Instrument in Adults With Type 2 Diabetes

Journal of Nursing Measurement ◽

10.1891/jnm-d-20-00137 ◽

2021 ◽

pp. JNM-D-20-00137

Author(s):

Lynnette Leeseberg Stamler ◽

Kathleen M. Hanna ◽

Kevin A. Kupzyk ◽

Cyrus DeSouza

Keyword(s):

Type 2 Diabetes ◽

Factor Analysis ◽

Content Analysis ◽

Confirmatory Factor Analysis ◽

Item Analysis ◽

Future Research ◽

Valid Measure ◽

Psychometric Characteristics ◽

Confirmatory Factor

Background and PurposeA promising, yet lengthy measure to identify mastery of patient-identified stress is Younger’s (1991, 1993) Mastery of Stress Instrument (MSI). With a goal for a parsimonious and valid measure, this study determined the psychometric properties of a reduced item instrument with adults diagnosed with type 2 diabetes.MethodsFirst, an expert content analysis was completed. Second, item and confirmatory factor analysis were completed with a sample of 200 adults with a diagnosis of type 2 diabetes.ResultsEight items were removed through content validity and seven items were removed with Item analysis. Factor analysis supported Younger’s four sub-concepts.ConclusionsFuture research with this revised MSI scale is advocated to identify those who may need strategies to increase their mastery of stress.

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Psychometric Properties of the Forgiveness Likelihood Scale among Portuguese Adolescents

Psychological Reports ◽

10.2466/pr0.100.4.1229-1232 ◽

2007 ◽

Vol 100 (3_suppl) ◽

pp. 1229-1232 ◽

Cited By ~ 2

Author(s):

Félix Neto ◽

Ana Veríssimo Ferreira ◽

Conceição Pinto

Keyword(s):

High School ◽

Factor Analysis ◽

High School Students ◽

Confirmatory Factor Analysis ◽

Psychometric Properties ◽

Cross Cultural ◽

Psychometric Characteristics ◽

School Students ◽

Confirmatory Factor ◽

Portuguese Adolescents

To facilitate use of the Forgiveness Likelihood Scale in cross-cultural studies, the psychometric characteristics of the translated scale were examined among 192 adolescents in Portugal (86 men and 106 women). The Forgiveness Likelihood Scale is a 10-item Likert-type scale designed to measure tendency to forgive across situations. Cronbach α was .89. Confirmatory factor analysis showed that the questionnaire was unidimensional among Portuguese high school students.

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Application of Confirmatory Factor Analysis for Correlate of Students Attitude, Self-Belief, Students Engagement in Mathematics Lessons and Mathematics Achievement

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i2.29.13814 ◽

2018 ◽

Vol 7 (2.29) ◽

pp. 535 ◽

Cited By ~ 1

Author(s):

Desi Rahmatina

Keyword(s):

Factor Analysis ◽

Mathematics Achievement ◽

Confirmatory Factor Analysis ◽

Latent Variables ◽

Negative Relationship ◽

Mathematics Lesson ◽

Analysis Model ◽

Factor Analysis Model ◽

Data Set ◽

Confirmatory Factor

The study aimed to propose the Confirmatory Factor Analysis via four latent variables : 1) Students Attitude toward mathematics, 2) Self-belief in mathematics, 3) Students engagement in mathematics lessons and 4) Mathematics Achievement and 19 observed variables and then we conduct to the correlations between latent variables and observed variables. The subjects were 5795 eight grades students from the result of the Trends in International Mathematics and Science Study (TIMSS) 2011 assessment conducted in Indonesia. Data Analysis were undertaken using the Lisrel software to examine the effect of students attitude toward mathematics, students self belief and students engagement in mathematics lesson for mathematics achievement. The proposed Confirmatory Factor Analysis model of the latent variables and observed variables fit well with the empirical data set (RMSEA = 0,071). The results of multivariate analyses has shown a strong negative relationship between student attitude toward mathematics, self-belief in mathematics and their mathematics achievement (t value = -6.32 and t = -6.10, respectively) and a strong positive relationship between students engagement in mathematics lesson with mathematics achievement (t value = 8,28).

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The Occupational Stress Inventory-Revised: Confirmatory factor analysis of the original inter-correlation data set and model

Personality and Individual Differences ◽

10.1016/j.paid.2009.10.024 ◽

2010 ◽

Vol 48 (3) ◽

pp. 351-353 ◽

Cited By ~ 5

Author(s):

R.E. Hicks ◽

M. Bahr ◽

D. Fujiwara

Keyword(s):

Factor Analysis ◽

Confirmatory Factor Analysis ◽

Occupational Stress ◽

Data Set ◽

Correlation Data ◽

Confirmatory Factor ◽

Stress Inventory

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Decentralization: Operationalization and measurement model

International Journal of Organization Theory and Behavior ◽

10.1108/ijotb-19-03-2016-b001 ◽

2016 ◽

Vol 19 (3) ◽

pp. 275-307 ◽

Cited By ~ 1

Author(s):

Boris Morozov

Keyword(s):

Factor Analysis ◽

Confirmatory Factor Analysis ◽

Hypothesis Testing ◽

Measurement Model ◽

Focus Of Attention ◽

Two Dimensions ◽

Data Set ◽

Proposed Model ◽

Confirmatory Factor

Decentralization has been a continual focus of attention of both scholars and practitioners for more than half a century. Even though there is a general agreement on what decentralization is, there is no consensus about how it should be measured. This article builds on the existing body of literature that specifies three major dimensions of decentralization: political, administrative, and economic. The article offers a measurement model that unifies these dimensions in a meaningful manner that allows for comparison across countries. The proposed model is then empirically tested using confirmatory factor analysis of a data set of 37 countries over the period 2000-2009. This factor analysis reveals that there are, in fact, only two dimensions of the decentralization process. The newly developed modelʼs index illustrates that the conceptually challenging processes of decentralization can be accurately measured and analyzed. The index can be used for hypothesis testing of the causality role of decentralization.

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