scholarly journals Dimensionality of the Wisconsin Schizotypy Scales-Brief Forms in College Students

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Eduardo Fonseca-Pedrero ◽  
Mercedes Paino ◽  
Javier Ortuño-Sierra ◽  
Serafín Lemos-Giráldez ◽  
José Muñiz
Keyword(s):  
College Students ◽  
Internal Structure ◽  
Structural Equation ◽  
Equation Modeling ◽  
Measuring Instruments ◽  
Magical Ideation ◽  
Final Sample ◽  
Confirmatory Factor ◽  
Physical Anhedonia ◽  
Wisconsin Schizotypy Scales

Wisconsin Schizotypy Scales are one of the most used measuring instruments for the assessment of psychometric risk for psychosis. The main goal of the present study was to analyze the internal structure of the Wisconsin Schizotypy Scales-Brief (WSS-B) forms and the reliability of the scores in a large sample of college students. The final sample was comprised by a total of 1349 students, 288 males, with a mean age of 20.48 years (SD = 2.58). The results indicated that the WSS-B scores presented adequate psychometric properties. Cronbach’s alfa coefficient for total scores in WSS-B ranged from 0.86 to 0.93. Analysis of the internal structure of the WSS-B, through confirmatory factor analysis and exploratory structural equation modeling, yielded a four factor solution (Magical Ideation, Perceptual Aberration, Social Anhedonia, and Physical Anhedonia) as the most adequate. Statistically significant differences in mean scores of WSS-B by sex were found. These results provided new validity evidence of the WSS-B scores in an independent sample of nonclinical young adults. The WSS-B seems to be useful, brief, and easy to administrate for the screening of extended psychosis phenotype in the general population.

Differential Item Functioning of the Full and Brief Wisconsin Schizotypy Scales in Asian, White, Hispanic, and Multiethnic Samples and Between Sexes

Assessment ◽  
2017 ◽  
Vol 26 (6) ◽  
pp. 1001-1013 ◽  
Author(s):  
David C. Cicero ◽  
Elizabeth A. Martin ◽  
Alexander Krieg
Keyword(s):  
Differential Item Functioning ◽  
Structural Equation ◽  
Self Report ◽  
Equation Modeling ◽  
Modeling Framework ◽  
Magical Ideation ◽  
Item Functioning ◽  
Multiple Indicator ◽  
Wisconsin Schizotypy Scales ◽  
Multiple Causes

The Wisconsin Schizotypy Scales, including their brief versions, are among the most commonly used self-report measures of schizotypy. Although they have been used extensively in many ethnic groups, few studies have examined their differential item functioning (DIF) across groups. The current study included 1,056 Asian, 408 White, 476 Multiethnic, and 372 Hispanic undergraduates. Unidimensional models of the brief Magical Ideation Scale and Perceptual Aberration Scales fit the data well. For both scales, global tests of measurement invariance provided mixed evidence, but few of the items displayed DIF across ethnicities or between sexes within a multiple indicator multiple causes model. For the full versions of the scales and the brief Revised Social Anhedonia Scale, multiple indicator multiple causes models within an exploratory structural equation modeling framework found that few of the items had DIF. These findings suggest that some of the items may have different psychometric properties across groups, but most items do not.

scholarly journals Hierarchical Models of Self-Concept across Genders and Sciences/Humanities for College Students in Taiwan

2013 ◽  
Vol 2013 ◽  
pp. 1-9
Author(s):  
Mei-Shiu Chiu
Keyword(s):  
College Students ◽  
Hierarchical Models ◽  
Structural Equation ◽  
Self Concept ◽  
Equation Modeling ◽  
National Database ◽  
Fields Of Study ◽  
Confirmatory Factor ◽  
Order Factor ◽  
Structural Invariance

The aim of this study is to examine the hierarchical model of self-concept (SC) using two operations (Models A and B). In Model A, global self-concept (GSC) is the higher-order factor of field-specific self-concepts (FSCs). In Model B, GSC is the predictor of the correlated FSCs. The data of 28,824 college students are obtained from the national database for higher education in Taiwan. The two models are examined by the use of total-group hierarchical confirmatory factor analysis (HCFA) and structural equation modeling (SEM), respectively. Multigroup HCFA and SEM are used to test whether the two models demonstrate measurement equivalence and structural invariance across female and male college students and across college students coming from different fields of study. The results of the analysis reveal three major findings. (1) The data fit Models A-B well for all the students as a whole. (2) Females and males are found not to be equivalent in the structure of both models. (3) Females from female-dominated humanities fields (education and business) are different from those in male-dominated sciences fields (engineering and natural sciences), while males from the four fields are similar in both models.

scholarly journals A New Story on the Multidimensionality of the MSPSS: Validity of the Internal Structure through Bifactor ESEM

2022 ◽  
Vol 19 (2) ◽  
pp. 935
Author(s):  
César Merino-Soto ◽  
Alicia Boluarte Carbajal ◽  
Filiberto Toledano-Toledano ◽  
Laura A. Nabors ◽  
Miguel Ángel Núñez-Benítez
Keyword(s):  
Internal Structure ◽  
Structural Equation ◽  
Perceived Social Support ◽  
Educational Institution ◽  
Detailed Examination ◽  
Equation Modeling ◽  
General Factor ◽  
Confirmatory Factor ◽  
Bifactor Models ◽  
Correlated Factors

The internal structure of the Multidimensional Scale of Perceived Social Support (MSPSS) in adolescents has been evaluated with some factorial analysis methodologies but not with bifactor exploratory structural equation modeling (ESEM), and possibly the inconsistency in the internal structure was dependent on these approaches. The objective of the study was to update evidence regarding its internal structure of MSPSS, by means of a detailed examination of its multidimensionality The participants were 460 adolescents from an educational institution in the Callao region, Lima, Peru. The structure was modeled using unidimensional, three-factor and bifactor models with confirmatory factor analysis (CFA) and ESEM approaches. The models showed good levels of fit, with the exception of the unidimensional model; however, the multidimensionality indicators supported the superiority of the bifactor ESEM. In contrast, the general factor was not strong enough, and the interfactorial correlations were substantially lower. It is concluded that the MSPSS can be interpreted by independent but moderately correlated factors, and there is possible systematic variance that potentially prevented the identification of a general factor.

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.

How Communication in Organizations Is Related to Foci of Commitment and Turnover Intentions

2020 ◽  
pp. 1-12
Author(s):  
Sebastian Holzwarth ◽  
George Gunnesch-Luca ◽  
Roman Soucek ◽  
Klaus Moser
Keyword(s):  
Organizational Communication ◽  
Turnover Intention ◽  
Structural Equation ◽  
Affective Commitment ◽  
Turnover Intentions ◽  
Equation Modeling ◽  
Cross Sectional ◽  
Confirmatory Factor ◽  
Communication In Organizations ◽  
Cohesion Theory

Abstract. The current study analyzes how two components of perceived organizational communication (vertical and horizontal) are related to employee turnover intentions via three types of affective commitment foci (organization, supervisor, and team). Using second-order confirmatory factor analysis and structural equation modeling techniques with a large cross-sectional dataset ( n = 3,317), our results show that, in line with social cohesion theory, vertical communication (e.g., supportiveness from the organization) is strongly related to affective organizational commitment, whereas horizontal communication (e.g., supportiveness from colleagues) is primarily related to affective team commitment. Additionally, both communication dimensions are related to affective supervisory commitment. Finally, these three foci of affective commitment incrementally explain and differentially mediate the relationship between perceived organizational communication and turnover intention.

Examining Psychosociocultural Influences as Predictors of Black College Students’ Academic Self-Concept and Achievement

2020 ◽  
pp. 009579842097979
Author(s):  
Samuel T. Beasley ◽  
Shannon McClain
Keyword(s):  
College Students ◽  
Academic Engagement ◽  
Structural Equation ◽  
Black College ◽  
Self Concept ◽  
Equation Modeling ◽  
Black College Students ◽  
Grade Point ◽  
Racial Centrality ◽  
Positive Direct

Using the psychosociocultural framework, this study concurrently examined the influence of psychological (academic self-concept and academic engagement attitudes), social (caring student-faculty relationships), and cultural variables (racial centrality and perceived university environment) on the academic achievement of Black college students. Participants were 247 Black collegians recruited from a large, Southwestern predominately White institution. Results of structural equation modeling largely supported hypothesized relationships between variables, accounting for 16% of the variance in grade point average (GPA), 75% of the variance in academic engagement, and 29% of the variance in academic self-concept. Results revealed two positive direct paths to GPA: (a) racial centrality and (b) academic self-concept; academic self-concept had a key role in facilitating indirect effects on academic engagement and GPA. Findings highlight multiple noncognitive predictors that can facilitate Black students’ academic functioning. Research and practice implications of these findings are outlined.

scholarly journals Analysis of Influencing Factors of College Students’ Intention to Repeated Blood Donation Based on Structural Equation Modeling

2021 ◽  
Author(s):  
Lingling Pan ◽  
Wei Hu ◽  
Wenjuan Han ◽  
Yingying Wang
Keyword(s):  
College Students ◽  
Structural Equation Modeling ◽  
Influencing Factors ◽  
Structural Equation ◽  
Blood Donation ◽  
Behavioral Control ◽  
Equation Modeling ◽  
Perceived Behavioral Control ◽  
Behavior Intention ◽  
Donation Behavior

AbstractTo research the influencing factors of college students' blood donation behavior intention and propose intervention strategies to improve the repeated blood donation rate of college students. Questionnaire survey was used to research and analyze the influencing factors of behavior intention. Amos 21.0 software was used to establish structural equation modeling and perform confirmatory factor analysis. SPSS 20.0 was used for statistic. The model was proved with highly adaptability, with χ2/df = 2.956 < 3. Factors influencing college students' intention of repeat blood donation behavior can be summarized into four: attitude, external motivation, advice-taking, and perceived behavioral control. Among them, attitude and perceived behavioral control have a great direct impact on behavioral intention, while the external motivation and recommendation acceptance have an indirect impact by influencing the other two factors. In view of those evaluation items with high path coefficient in each factor, we can develop recruitment strategies to influence college students’ repeated blood donation behavior and provide scientific suggestions for improving their repeated blood donation rate.

A Comparison of Reliability Estimation Based on Confirmatory Factor Analysis and Exploratory Structural Equation Models

2021 ◽  
pp. 001316442110089
Author(s):  
Yuanshu Fu ◽  
Zhonglin Wen ◽  
Yang Wang
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Structural Equation ◽  
Reliability Estimation ◽  
Model Fit ◽  
Equation Modeling ◽  
Factor Loadings ◽  
Reliability Estimates ◽  
Confirmatory Factor ◽  
Composite Reliability

Composite reliability, or coefficient omega, can be estimated using structural equation modeling. Composite reliability is usually estimated under the basic independent clusters model of confirmatory factor analysis (ICM-CFA). However, due to the existence of cross-loadings, the model fit of the exploratory structural equation model (ESEM) is often found to be substantially better than that of ICM-CFA. The present study first illustrated the method used to estimate composite reliability under ESEM and then compared the difference between ESEM and ICM-CFA in terms of composite reliability estimation under various indicators per factor, target factor loadings, cross-loadings, and sample sizes. The results showed no apparent difference in using ESEM or ICM-CFA for estimating composite reliability, and the rotation type did not affect the composite reliability estimates generated by ESEM. An empirical example was given as further proof of the results of the simulation studies. Based on the present study, we suggest that if the model fit of ESEM (regardless of the utilized rotation criteria) is acceptable but that of ICM-CFA is not, the composite reliability estimates based on the above two models should be similar. If the target factor loadings are relatively small, researchers should increase the number of indicators per factor or increase the sample size.

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