scholarly journals Validating the University Student Engagement Model through Structural Equation Modeling

2018 ◽  
Vol 5 (4) ◽  
pp. 318 ◽  
Author(s):  
Hafsa Mzee Mwita
Keyword(s):  
Structural Equation Modeling ◽  
Student Engagement ◽  
Structural Equation ◽  
Factor Model ◽  
University Student ◽  
Equation Modeling ◽  
Psychological Constructs ◽  
Confirmatory Factor ◽  
The University ◽  
Behavior And Cognition

<p><em>The main purpose </em><em>of this study is to investigate whether emotional, cognitive and behavioral engagements, represents three conceptually and empirically distinct psychological constructs when studied within the same domain. This paper reports part of the findings from a major study entitled “Predictors of Self-Handicapping Behavior among Muslim Students”. Testing for factorial equivalence of scores from a measuring instrument was carried-out through structural equation modeling by using AMOS version 16.</em><em> </em><em>Results of Confirmatory Factor Analysis of responses from 790 undergraduates prove that the SEM three factor model of University Student Engagement (USE) is empirically fit and reliable, which also supports the argument that emotion, behavior and cognition are the student engagement manifestations of an interrelated constellation of academic student engagement. </em></p>

scholarly journals Factor Structure of the Athletic Identity Measurement Scale with Athletes with Disabilities

1997 ◽  
Vol 14 (1) ◽  
pp. 74-82 ◽  
Author(s):  
Jeffrey J. Martin ◽  
Robert C. Eklund ◽  
Carol Adams Mushett
Keyword(s):  
Factor Analysis ◽  
Structural Equation Modeling ◽  
Sport Psychology ◽  
Structural Equation ◽  
Factor Model ◽  
Athletic Identity ◽  
Measurement Scale ◽  
Equation Modeling ◽  
Confirmatory Factor ◽  
Athletes With Disabilities

Individuals who perceive themselves as “athletes” are thought to have self-schemas composed of, in part, an athletic identity (Brewer, Van Raalte, & Linder, 1993). The recent development of the Athletic Identity Measurement Scale (AIMS) has allowed sport psychology researchers to assess athletic identity. Research with adolescent athletes with disabilities has suggested that the AIMS is composed of 4 factors (Martin, Mushett, & Eklund, 1994). The purpose of the current study was to further examine the psychometric properties of the AIMS. Seventy-eight international swimmers (34 females, 44 males) with disabilities, ranging in age from 12 to 44 (M = 23.4 years), participated in the present study. Using structural equation modeling procedures, a confirmatory factor analysis determined that the data fit the 4-factor model specified in the Martin et al. (1994) study, thus providing support for the multidimensionality of the AIMS.

A Psychometric Study of the Quality Perception Questionnaire

2012 ◽  
Vol 71 (2) ◽  
pp. 101-106 ◽  
Author(s):  
Raffaele Cioffi† ◽  
Anna Coluccia ◽  
Fabio Ferretti ◽  
Francesca Lorini ◽  
Aristide Saggino ◽  
...  
Keyword(s):  
Structural Equation ◽  
Factor Model ◽  
Equation Modeling ◽  
Fit Indices ◽  
Quality Perception ◽  
Italian Survey ◽  
Confirmatory Factor ◽  
Instrument Measuring ◽  
Hospital Structures

The present paper reexamines the psychometric properties of the Quality Perception Questionnaire (QPQ), an Italian survey instrument measuring patients’ perceptions of the quality of a recent hospital admission experience, in a sample of 4400 patients (Mage = 56.42 years; SD = 19.71 years, 48.8% females). The 14-item survey measures four factors: satisfaction with medical doctors, nursing staff, auxiliary staff, and hospital structures. First, we tested two models using a confirmatory factor analysis (structural equation modeling): a four orthogonal factor and a four oblique factor model. The SEM fit indices and the χ² difference suggested the acceptance of the second model. We then did a simulation using a bootstrap with 1000 replications. Results confirmed the four oblique factor solution. Third, we tested whether there were significant differences with respect to age or sex. The multivariate general linear model showed no significant differences in the factors with respect to sex or age.

Working Memory, Mental Prospection, Time Orientation, and Cognitive Insight

2013 ◽  
Vol 34 (3) ◽  
pp. 159-169 ◽  
Author(s):  
Sevtap Cinan ◽  
Aslı Doğan
Keyword(s):  
Working Memory ◽  
Structural Equation ◽  
Factor Model ◽  
Time Orientation ◽  
Equation Modeling ◽  
Cognitive Insight ◽  
Confirmatory Factor ◽  
Negative Effect ◽  
Positive Effect ◽  
Three Factor

This research is new in its attempt to take future time orientation, morningness orientation, and prospective memory as measures of mental prospection, and to examine a three-factor model that assumes working memory, mental prospection, and cognitive insight are independent but related higher-order cognitive constructs by using confirmatory factor analysis (CFA). The three-factor model produced a good fit to the data. An alternative one-factor model was tested and rejected. The results suggest that working memory and cognitive insight are distinguishable, related constructs, and that both are distinct from, but negatively associated with, mental prospection. In addition, structural equation modeling (SEM) showed that working memory had a strong positive effect on cognitive insight and a moderate negative effect on mental prospection.

Further Insights Into the German Version of the Multidimensional Assessment of Interoceptive Awareness (MAIA)

2019 ◽  
Vol 35 (3) ◽  
pp. 317-325 ◽  
Author(s):  
Dorota Reis
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Equation Modeling ◽  
Interoceptive Awareness ◽  
Multidimensional Assessment ◽  
New Instrument ◽  
Confirmatory Factor ◽  
Complex Models ◽  
Approximate Zero ◽  
Bayesian Structural Equation Modeling

Abstract. Interoception is defined as an iterative process that refers to receiving, accessing, appraising, and responding to body sensations. Recently, following an extensive process of development, Mehling and colleagues (2012) proposed a new instrument, the Multidimensional Assessment of Interoceptive Awareness (MAIA), which captures these different aspects of interoception with eight subscales. The aim of this study was to reexamine the dimensionality of the MAIA by applying maximum likelihood confirmatory factor analysis (ML-CFA), exploratory structural equation modeling (ESEM), and Bayesian structural equation modeling (BSEM). ML-CFA, ESEM, and BSEM were examined in a sample of 320 German adults. ML-CFA showed a poor fit to the data. ESEM yielded a better fit and contained numerous significant cross-loadings, of which one was substantial (≥ .30). The BSEM model with approximate zero informative priors yielded an excellent fit and confirmed the substantial cross-loading found in ESEM. The study demonstrates that ESEM and BSEM are flexible techniques that can be used to improve our understanding of multidimensional constructs. In addition, BSEM can be seen as less exploratory than ESEM and it might also be used to overcome potential limitations of ESEM with regard to more complex models relative to the sample size.

On the Structure of Affect

2021 ◽  
Vol 229 (1) ◽  
pp. 24-37 ◽  
Author(s):  
Nadine Wedderhoff ◽  
Timo Gnambs ◽  
Oliver Wedderhoff ◽  
Tanja Burgard ◽  
Michael Bošnjak
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Factor Model ◽  
Self Report ◽  
Equation Modeling ◽  
Positive And Negative Affect ◽  
Correlation Matrices ◽  
The World ◽  
Best Fit ◽  
Cross National

Abstract. The Positive and Negative Affect Schedule (PANAS; Watson et al., 1988 ) is a popular self-report questionnaire that is administered all over the world. Though originally developed to measure two independent factors, different models have been proposed in the literature. Comparisons among alternative models as well as analyses concerning their robustness in cross-national research have left an inconclusive picture. Therefore, the present study evaluates the dimensionality of the PANAS and differences between English and translated versions of the PANAS using a meta-analytic structural equation modeling approach. Correlation matrices from 57 independent samples ( N = 54,043) were pooled across subsamples. For both English and non-English samples, a correlated two-factor model including correlated uniquenesses provided the best fit. However, measurement invariance analyses indicated differences in factor loadings between subsamples. Thus, cross-national application of the PANAS might only be justified if measurement equivalence was explicitly tested for the countries at hand.

scholarly journals Modeling and Analysis of the Motivations of Fast Fashion Consumers in Relation to Innovativeness

2016 ◽  
Vol 16 (4) ◽  
pp. 205-213
Author(s):  
Canan Saricam ◽  
Nazan Erdumlu
Keyword(s):  
Factor Analysis ◽  
Structural Equation Modeling ◽  
Confirmatory Factor Analysis ◽  
Structural Equation ◽  
Motivational Factors ◽  
Equation Modeling ◽  
Fast Fashion ◽  
Modeling And Analysis ◽  
Confirmatory Factor ◽  
The Relationship

Abstract In this study, fast fashion concept is investigated in order to understand the motivations of the consumers that make them adopt these products because of their willingness for the innovativeness. The relationship between the motivational factors which were named as “Social or status image” and “Uniqueness” as expressions of individuality, “Conformity” and the willingness for “Innovativeness” is analyzed using a conceptual model. Exploratory factor analysis, confirmatory factor analysis and structural equation modeling were used to analyze and validate the model. The data used for the study was obtained from 244 people living in Turkey. The findings showed that the motivational factors “Social or status image” and “Uniqueness” as expressions of individuality are influential on the consumers’ willingness for “Innovativeness”.

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