scholarly journals Reconsidering the structure of the questionnaire for eudaimonic well-being using wide age-range Japanese adult sample: An exploratory analysis

2022 ◽  
Vol 10 (1) ◽  
Author(s):  
Yu Ishii ◽  
Ryota Sakakibara ◽  
Aiko Komoto Kubota ◽  
Kazuhiro Yamaguchi
Keyword(s):  
Factor Structure ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Age Groups ◽  
Well Being ◽  
Equation Modeling ◽  
Fit Indices ◽  
Japanese Adult ◽  
Psychological Construct ◽  
Wide Range

Abstract Background An increasing amount of research is now highlighting the importance of approaching issues of happiness through eudaimonic well-being. However, the literature does not conclusively show a full understanding of the construct of eudaimonic well-being, as previous studies primarily focused on younger samples from Western countries and only a few studies have attempted to explore its psychological construct through exploratory approaches. Therefore, we conducted a survey among a wide range of age groups in Japan to capture the psychological construct of eudaimonic well-being, through an exploratory analytic approach using Questionnaire for Eudaimonic Wellbeing (QEWB). Methods A total of 1126 Japanese participants (580 females, 546 males) were included for analysis. Participants were divided into three age groups according to their age, including 10s to 20s (18–29 years), 30s to 40s (30–49 years) and 50s to 60s (50–69 years). After narrowing down the total number of factors by exploratory structural equation modeling (ESEM), we conducted an ESEM and bifactor ESEM with oblique goemin and oblique bi-geomin rotations for choosing and assessing the final model based on the rotated results and its interpretability. Results The results of a parallel analysis and goodness-of-fit indices obtained by ESEM indicated that the QEWB consisted of three or more factors. Both a three-to-six factor and bifactor ESEM with oblique goemin rotation showed that three-factor structure for the 30s to 40s and 50s to 60s and four-factor structure for the 10s to 20s should be chosen, respectively. “Deep and Meaningful Engagement,” a factor only relevant to the 10s to 20s may be an expanded version of what original paper called the Intense Involvement in Activities, with more emphasis on the enthusiastic attitude one has towards activities. Conclusions The structure of eudaimonic well-being may differ across cultures and ages, thus requiring further investigation in the field.

scholarly journals A Model on the Contribution of School Assets to the Achievement of Adolescents’ Well-Being and Academic Performance

2017 ◽  
Vol 20 ◽  
Author(s):  
Miguel-Ángel Pertegal ◽  
Alfredo Oliva
Keyword(s):  
Life Satisfaction ◽  
Academic Performance ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
School Connectedness ◽  
Well Being ◽  
Self Report ◽  
Equation Modeling ◽  
Fit Indices ◽  
Key Factor

AbstractThe aim of this study was to examine a model on the contribution of school assets on the development of adolescent´s well-being and school success. The sample comprised 1944 adolescents (893 girls and 1051 boys) aged between 12 and 17 years (M= 14.4;SD= 1.13), from secondary schools in Western Andalusia, which completed some self-report questionnaires. The results of structural equation modeling showed the goodness of fit of the initial theoretical model. This model confirmed the importance of school connectedness as a key factor in the relationships between other school assets (social climate; clarity of the rules and values, and positive opportunities and empowerment) and commitment to learning, academic performance and life satisfaction. However, the re-specification of the initial model considered two complementary paths with theoretical sense: first, a direct influence between clarity of the rules and values and commitment to learning, and second, between academic performance and life satisfaction. This model obtained better goodness of fit indices than the first one: χ2= 16.32;gl= 8;p= .038; χ2/gl= 2.04; SRMR = .018; RSMEA = .023 (95% C.I. = .005; 040); NNFI = .98; CFI = .99. From our study, the need to invest in initiatives focused on the promotion of adolescents’ links with their school emerges as a key goal to contribute towards, at the same time, both a good academic performance and a better life satisfaction.

Structural Equation Modeling: An Alternative to Traditional Validation Techniques

1986 ◽  
Vol 14 (4) ◽  
pp. 345-352
Author(s):  
Margaret E. Bell ◽  
Jean A. Massey
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Statistical Significance ◽  
Equation Modeling ◽  
Fit Indices ◽  
T Values ◽  
Conditions Of Learning ◽  
Nursing Course ◽  
Cardiovascular Nursing

Validation of the sequencing of objectives is an important step in structural design. Prior statistical techniques, such as the reproducibility coefficient, have yielded only summary information. In contrast, structural equation modeling provides both goodness-of-fit indices and effect coefficients for links or paths between time-ordered events, i.e., objectives. Discussed here is the application of structural equation modeling to a set of objectives in a senior-level cardiovascular nursing course. Consistent with the theory-based requirement of structural equation modeling, the objectives were developed using Robert Gagné's conditions of learning. Also discussed is the use of “t” values, which indicate statistical significance of the paths, for testing instructional links in the learning model.

Measuring fairness in franchisor-franchisee relationship: a confirmatory approach

2017 ◽  
Vol 45 (2) ◽  
pp. 158-176 ◽  
Author(s):  
Ateeque Shaikh ◽  
Saswata Narayan Biswas ◽  
Vanita Yadav ◽  
Debiprasad Mishra
Keyword(s):  
Factor Structure ◽  
Structural Equation ◽  
Large Scale ◽  
Goodness Of Fit ◽  
Threshold Level ◽  
Fit Indices ◽  
Validity And Reliability ◽  
Content Type ◽  
Perceptions Of Fairness ◽  
Three Factor

Purpose The purpose of this paper is to develop, test and validate a measure of fairness in the context of franchisor-franchisee relationship and test for the dimensionality of fairness. Design/methodology/approach The authors surveyed 300 franchisees of a large-scale franchisor in India. The authors employ confirmatory factor analysis (CFA) to analyse the data. Findings The authors tested four models of the fairness construct through CFA using structural equation modelling. The three-factor corrected model of the fairness construct exhibits comparatively better goodness of fit indices as compared to the other correlated models of the fairness construct. It clears the threshold level of validity and reliability test. The findings of the study suggest that the factor structure of fairness is three-factor correlated model with aspects of procedural fairness and informational fairness getting subsumed into one construct. Research limitations/implications Factor structure of fairness construct differs with earlier empirical research findings with both interpersonal fairness and informational fairness subsuming into each other to form one construct. Practical implications This measure can be utilized by franchisee managers to track perceptions of fairness among franchisees to manage the franchise relationship in a better way. Franchisees expect information sharing from the franchisor and not the representative of the franchisor. Originality/value To the best of the authors’ knowledge, this study is the first to develop a valid and reliable measure of fairness construct in the context of franchise relationship. This study also identifies factor structure of fairness construct.

scholarly journals Mengakomodasi Efek Metode dalam Pengujian Validitas Konstruk Melalui Analisis Faktor Konfirmatori

2017 ◽  
Vol 1 (1) ◽  
pp. 37
Author(s):  
Wahyu Widhiarso
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Equation Modeling ◽  
Fit Indices ◽  
Method Effect ◽  
Confirmatory Factor ◽  
Method Effects ◽  
Item Writing

Literatures in the field of psychometrics recommend researchers to employvarious of methods on measuring individual attributes. Ideally,each methods are complementary and measuresthe construct designed to be measured. However, some problems arise when among the methods is unique and unrelated to the construct being measured. The uniqueness of method can lead what is called the method effect. In testing construct validity using confirmatory factor analysis, the emergence of this effect tend to reducing the goodness of fit indices of the model. There are many ways to solve these problem, one of themis controling the method effects and accommodate it to the model. This paper introduces how to accommodate method effecton the confirmatory factor analysis using structural equation modeling. In the application section, author identify the emergence of method effects due to the differences item writing direction (favorable-unfavorable). The analysis showed that method effectemerge from different writing direction.

scholarly journals Correcting the Bias of the Root Mean Squared Error of Approximation under Missing Data

2018 ◽  
Author(s):  
Cailey Elizabeth Fitzgerald ◽  
Ryne Estabrook ◽  
Daniel Patrick Martin ◽  
Andreas Markus Brandmaier ◽  
Timo von Oertzen
Keyword(s):  
Missing Data ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Mean Squared Error ◽  
Equation Modeling ◽  
Fit Indices ◽  
Root Mean Squared Error ◽  
Squared Error ◽  
Acceptable Model ◽  
Downward Bias

Missing data are ubiquitous in both small and large datasets. Missing data may come about as a result of coding or computer error, participant absences, or it may be intentional, as in planned missing designs. We discuss missing data as it relates to goodness-of-fit indices in Structural Equation Modeling (SEM), specifically the effects of missing data on the Root Mean Squared Error of Approximation (RMSEA). We use simulations to show that naive implementations of the RMSEA have a downward bias in the presence of missing data and, thus, overestimate model goodness-of-fit. Unfortunately, many state-of-the-art software packages report the biased form of RMSEA. As a consequence, the community may have been accepting a much larger fraction of models with non-acceptable model fit. We propose a bias-correction for the RMSEA based on information-theoretic considerations that take into account the expected misfit of a person with fully observed data. This results in an RMSEA which is asymptotically independent of the proportion of missing data for misspecified models. Importantly, results of the corrected RMSEA computation are identical to naive RMSEA if there are no missing data.

scholarly journals Psychological Adjustment of Expatriate Children in Cultural Transitions

2020 ◽  
Vol 11 (1) ◽  
pp. 1-21
Author(s):  
Anu Warinowski ◽  
Eero Laakkonen
Keyword(s):  
Survey Data ◽  
Psychological Adjustment ◽  
Factor Structure ◽  
Structural Equation ◽  
School Success ◽  
Depression Scale ◽  
Well Being ◽  
Equation Modeling ◽  
Affective Factors ◽  
Cultural Transitions

The aim of the current study was to define the factorial structure of the psychological adjustment (PA) of Finnish expatriate children (EC) and to construct a model consisting of three child-level variables (age, school success, and attitude toward moving). Survey data concerning Finnish EC (N = 324) who had lived temporarily abroad were gathered from the EC’s parents. The mean age of the children was 4.8 years in the expatriation context and 8.2 years in the repatriation context. PA was examined using the Zung Self-Rating Depression Scale (ZSDS). Survey data were subject to a confirmatory factor analysis (CFA) and structural equation modeling (SEM). A hypothesized two-factor structure (physiological and affective factors) of PA was fitted for the sample using the CFA. A SEM of PA was presented, where the child-level explanatory variables were the age of the child, school success, and attitude toward moving. The main findings were the following: First, there is a two-factor structure of Finnish EC’s PA with both physiological and affective factors. Second, a model of PA with three child-level variables (age, school success, and attitude toward moving) was constructed. The results contribute to the understanding of PA in general and EC’s PA in particular. This study increases our understanding of EC’s PA in unique and novel contexts of dual cultural transitions. This comprehension is important in an increasingly globalized world, especially in clinical and other support contexts, where professionals work for children’s mental well-being.

scholarly journals Resilience Analysis of Crisis in Medical Environments: A Structural Equation Modeling based on Crisis Management Components

2022 ◽  
Author(s):  
SAMIRA GHIYASI ◽  
FATEMEH VERDI BAGHDADI ◽  
FARSHAD HASHEMZADEH ◽  
AHMAD SOLTANZADEH
Keyword(s):  
Structural Equation Modeling ◽  
Crisis Management ◽  
Work Experience ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Equation Modeling ◽  
Fit Indices ◽  
Cross Sectional ◽  
Resilience Index ◽  
The Impact

Enhancing the index of crisis resilience is one of the key goals in medical environments. Various parameters can affect crisis resilience. The current study was designed to analyze crisis resilience in medical environments based on the crisis management components. This cross-sectional and descriptive-analytical study was performed in 14 hospitals and medical centers, in 2020. A sample size of 343.5 was determined based on the Cochran's formula. We used a 44-item crisis management questionnaire of Azadian et al. to collect data. The components of this questionnaire included management commitment, error learning, culture learning, awareness, preparedness, flexibility, and transparency. The data was analyzed based on the structural equation modeling approach using IBM SPSS AMOS v. 23.0. The participants’ age and work experience mean were 37.78±8.14 and 8.22±4.47 years. The index of crisis resilience was equal to 2.96±0.87. The results showed that all components of crisis management had a significant relationship with this index (p <0.05). The highest and lowest impact on the resilience index were related to preparedness (E=0.88) and transparency (E=0.60). The goodness of fit indices of this model including RMSEA, CFI, NFI, and NNFI (TLI) was 2.86, 0.071, 0.965, 0.972, and 0.978. The index of crisis resilience in the medical environments was at a moderate level. Furthermore, the structural equation modeling findings indicated that the impact of each component of crisis management should be considered in prioritizing measures to increase the level of resilience.  

scholarly journals Psychometric Properties of the Adult Self-Report: Data from over 11,000 American Adults

Stats ◽  
2020 ◽  
Vol 3 (4) ◽  
pp. 465-474
Author(s):  
Michelle Guerrero ◽  
Matt Hoffmann ◽  
Laura Pulkki-Råback
Keyword(s):  
Measurement Invariance ◽  
Structural Equation ◽  
Age Groups ◽  
Self Report ◽  
Equation Modeling ◽  
Future Research ◽  
Fit Indices ◽  
Invariance Testing ◽  
Report Data ◽  
Self Report Data

The first purpose of this study was to examine the factor structure of the Adult Self-Report (ASR) via traditional confirmatory factor analysis (CFA) and contemporary exploratory structural equation modeling (ESEM). The second purpose was to examine the measurement invariance of the ASR subscales across age groups. We used baseline data from the Adolescent Brain Cognitive Development study. ASR data from 11,773 participants were used to conduct the CFA and ESEM analyses and data from 11,678 participants were used to conduct measurement invariance testing. Fit indices supported both the CFA and ESEM solutions, with the ESEM solution yielding better fit indices. However, several items in the ESEM solution did not sufficiently load on their intended factors and/or cross-loaded on unintended factors. Results from the measurement invariance analysis suggested that the ASR subscales are robust and fully invariant across subgroups of adults formed on the basis of age (18–35 years vs. 36–59 years). Future research should seek to both CFA and ESEM to provide a more comprehensive assessment of the ASR.

scholarly journals PENGARUH REPUTASI SEBAGAI VARIABEL INTERVENING TERHADAP KINERJA PERUSAHAAN PADA PT.TELKOM KEBUMEN

2018 ◽  
Vol 17 (1) ◽  
pp. 41-53
Author(s):  
Sri Wahyuningsih
Keyword(s):  
Corporate Governance ◽  
Business Ethics ◽  
Social Responsibility ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Structural Model ◽  
Well Being ◽  
Equation Modeling ◽  
Future Research ◽  
Telecommunication Service

The purpose of this study is to investigate the influence of social responsibility, etiuka relatives, on the reputation of corporate governance and its impact on the performance of the company PT. Telkom Indonesia Branch Kebumen. The analytical tool used Structural Equation Modeling (SEM). The results of this study show that the reputation of social responsibility affects the reputation accepted. This is indicated by the value of CR = 2.514 and p = 0.012 or significant at ½ α = 0.05 t table = ± 1.980. Thus, the social responsibility variables formed by indicators of ethical codes, economic well-being, contributions and participant experiences have a significant influence on reputation. Further business ethics affects the accepted reputation. This is indicated by the value of CR = 2.872 and p = 0.004 or significant at  ½ α = 0.05 t table = ± 1.980. Thus the business ethics variables formed by the indicators: Product quality, product trials, respect for human dignity, cultural integrity of the customer has an influence on reputation. Corporate governance affects acceptable reputation. This is indicated by the value of CR = 3.241 and p = 0.001 or significant at ½ α = 0.05 t table = ± 1.980. thus corporate governance variables formed by the indicators: Company competence, openness and transparency, policy implementation, corporate policy, confidence in top management, knowledge and ability of human resources. Reputation, effect on company performance accepted. This is indicated by the value of CR = 13.933 and p = 0,000 or significant at ½ α = 0.05 t table = ± 1.980. Thus the reputation variable formed by the Company's Vision indicators, the product offered, the emotional closeness of the customer to the company, the company's financial capability and confidence in the employee. The limitations of this study on the structural model used, this model has been well seen from the test of cofirmatory and goodness-of-fit. but it is better for the company's performance topics to dig deeper into the variables and indicators used. Future research may also consider research objects that will be used not only in telecommunication service companies but can be developed in other business organizations.   Key word: Reputation and Corporate Performance

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