scholarly journals BOOTSTRAPPING WITH SMALL SAMPLES IN STRUCTURAL EQUATION MODELING: GOODNESS OF FIT AND CONFIDENCE INTERVALS

2014 ◽  
Author(s):  
◽  
Craig Krebsbach
Keyword(s):  
Structural Equation Modeling ◽  
Confidence Intervals ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Small Samples ◽  
Equation Modeling

scholarly journals Explanation of Children’s Health through Parents’ Mental Health and Job Satisfaction by Structural Equation Modeling

2016 ◽  
Vol 9 (2) ◽  
pp. 166
Author(s):  
Majid Golzarpour ◽  
Meroe Vameghi ◽  
Homeira Sajjadi ◽  
Gholamreza Ghaedamini Harouni
Keyword(s):  
Mental Health ◽  
Job Satisfaction ◽  
Structural Equation Modeling ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
General Health Questionnaire ◽  
Children's Health ◽  
Children’S Health ◽  
Equation Modeling ◽  
Health Questionnaire

<p><strong>BACKGROUND:</strong> Worldwide, much evidence exists on the influence of parents’ socioeconomic conditions, including employment, on children’s health. However, the mechanisms for this affect are still being investigated. Few studies have been conducted in Iran to investigate this issue. This study investigated working conditions, job satisfaction, and mental health of employed people and the association between these variables and their children’s health.<strong></strong></p><p><strong>MATERIALS &amp; METHODS:</strong> In this correlational work, 200 male and female staff of the official part of Educational Organization and the schools of Mashhad with children aged 5-18 years was randomly selected. The data were gathered using a demographic questionnaire, the 20-item Minnesota Job Satisfaction Questionnaire, the 28-item General Health Questionnaire, and the 28-item Child Health Questionnaire. The data were then analyzed using SPSS. The associations under study were investigated by structural equation modeling in AMOS.<strong></strong></p><p><strong>RESULTS:</strong> Approximately 17% of the variation in the parents’ job satisfaction could be explained by the parents’ insurance, income, and work hours; 6% of the variation in their mental health was explained by job satisfaction, and 26% of the variation in children’s health was directly explained by the parents’ job satisfaction and mental health. However, approximately 32.2% of the variation in children’s health could be explained in the light of the direct effect of the parents’ mental health and direct and indirect effects of the parents’ job satisfaction. The goodness of fit index was 0.94.</p><p><strong>CONCLUSION:</strong> Parents’ job satisfaction was associated with and considerably explained children’s health. Although this finding may be partially related to the job satisfaction effect on mental health, the reasons for the affect of job satisfaction on children’s health and the potential mechanisms of this association require further studies.<strong></strong></p>

scholarly journals MODEL PENGUKURAN TINGKAT KEPERCAYAAN PELANGGAN (ONLINE TRUST) TERHADAP SITUS E-COMMERCE (Studi Kasus pada Pelanggan E-Commerce di Provinsi Bali)

2018 ◽  
Vol 1 (3) ◽  
pp. 100
Author(s):  
I Made Endra Wiartika Putra ◽  
Gede Rasben Dantes ◽  
I Made Candiasa
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Equation Modeling ◽  
Snowball Sampling ◽  
Cronbach’S Alpha ◽  
Purposive Sampling ◽  
Online Trust ◽  
Cronbach's Alpha ◽  
Fit Index

Penelitian ini bertujuan untuk mengetahui model pengukuran tingkat kepercayaan pelanggan terhadap situs e-commerce. Langkah awal yang dilakukan yaitu identifikasi faktor-faktor yang mempengaruhi kepercayaan pelanggan melalui studi literatur dan studi empirik untuk menentukan model analisis terhadap kepuasan pelanggan. Faktor yang mempengaruhi kepercayaan pelanggan untuk bertransaksi secara online yaitu pengetahuan konsumen terhadap e-commerce, reputasi penjual, resiko dalam transaksi, kemudahan penggunaan e-commerce, jaminan sistem, sikap/perilaku terhadap sistem dan sistem keamanan. Populasi dalam penelitian ini adalah masyarakat Provinsi Bali menggunakan metode purposive sampling dan snowball sampling dengan kriteria responden pernah berkunjung dan melakukan transaksi di e-commerce yang ada di Indonesia lebih dari 3 kali. Instrumen penelitian berupa kuesioner dengan data interval berskala 5 Likert. Instrumen terlebih dahulu diuji validitas isi dengan metode Robert Gregory, validitas empiris menggunakan rumus product moment, reliabilitas instrument menggunakan Cronbach’s Alpha, dan menghasilkan 59 pernyataan yang dapat digunakan untuk pengambilan data. Jumlah responden yang digunakan dalam penelitian ini adalah sebanyak 126 responden. Teknik analisis data, pengujian hipotesis dan pengujian model menggunakan metode Structural Equation Modeling dengan bantuan aplikasi SPSS AMOS 21. Hasil penelitian ini melalui pengujian hipotesis menunjukkan bahwa pengetahuan tentang situs e-commerce dan perlindungan keamanan berpengaruh negatif dan tidak signifikan terhadap kepercayaan pelanggan. Resiko, kemudahan e-commerce, jaminan sistem dan sistem keamanan bukan menjadi sesuatu yang penting untuk dipertimbangkan dalam meningkatkan kepercayaan pelanggan karena pengaruhnya tidak signifikan. Reputasi yang dirasakan dan sikap merupakan hal yang perlu diperhatikan dan paling berpengaruh terhadap kepercayaan pelanggan pelanggan. Hasil penelitian ini kemudian diuji menggunakan goodness of fit index dan menghasilkan bahwa model penelitian tersebut dapat diterima dan dapat digunakan untuk meningkatkan keinginan pelanggan untuk bertransaksi online

scholarly journals Cutoff criteria for overall model fit indexes in generalized structured component analysis

2020 ◽  
Vol 8 (4) ◽  
pp. 189-202
Author(s):  
Gyeongcheol Cho ◽  
Heungsun Hwang ◽  
Marko Sarstedt ◽  
Christian M. Ringle
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Component Analysis ◽  
Model Fit ◽  
Equation Modeling ◽  
Generalized Structured Component Analysis ◽  
Root Mean Square Residual ◽  
Fit Indexes ◽  
Cutoff Criteria

AbstractGeneralized structured component analysis (GSCA) is a technically well-established approach to component-based structural equation modeling that allows for specifying and examining the relationships between observed variables and components thereof. GSCA provides overall fit indexes for model evaluation, including the goodness-of-fit index (GFI) and the standardized root mean square residual (SRMR). While these indexes have a solid standing in factor-based structural equation modeling, nothing is known about their performance in GSCA. Addressing this limitation, we present a simulation study’s results, which confirm that both GFI and SRMR indexes distinguish effectively between correct and misspecified models. Based on our findings, we propose rules-of-thumb cutoff criteria for each index in different sample sizes, which researchers could use to assess model fit in practice.

Organizational Commitment As Influenced by Leadership Behavior of Administrators, Job Satisfaction and Burnout of Teachers: A Structural Equation Modeling

10.17158/228 ◽  
2012 ◽  
Vol 18 (1) ◽  
Author(s):  
Felix C. Chavez, Jr.
Keyword(s):  
Job Satisfaction ◽  
Structural Equation Modeling ◽  
Organizational Commitment ◽  
Structural Equation ◽  
Quantitative Research ◽  
Goodness Of Fit ◽  
Leadership Behavior ◽  
Stepwise Multiple Regression ◽  
Equation Modeling ◽  
Best Fit

This study was conducted to determine the best fit model of organizational commitment. Specifically, it established the interrelationship among leadership behavior, job satisfaction, burnout, and organizational commitment. Quantitative research design was utilized in this study. The data were gathered from the teachers among the randomly selected academic institutions in Region XI, Philippines. Moreover, sets of survey questionnaires were used as instruments to obtain information from the participants. Pearson product moment correlation was used to find the significance of the relationship between the independent and dependent variables. Stepwise multiple regression analysis was used to identify the variables that best predict organizational commitment and likewise Structural Equation Modeling was used to identify the model that best fits organizational commitment. The findings revealed that the over-all leadership behavior of administrators and organizational commitment of teachers were high. On the other hand, the job satisfaction of teachers was moderate and their degree of burnout was low. Furthermore, the leadership behavior, job satisfaction, and burnout were highly correlated with organizational commitment, and found to be significant predictors of organizational commitment. Finally, the best fit model of organizational commitment was the Hypothesized Model 5, which passed all the goodness of fit indices criteria.

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.

scholarly journals Nurses’ Patient-Centeredness and Perceptions of Care among Medicaid Patients in Hospital Obstetrical Units

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Stephen J. Aragon ◽  
Liana J. Richardson ◽  
Wanda Lawrence ◽  
Sabina B. Gesell
Keyword(s):  
Structural Equation Modeling ◽  
Standard Deviation ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
The United States ◽  
Equation Modeling ◽  
Patient Centeredness ◽  
Patients Satisfaction ◽  
Random Samples ◽  
Multigroup Structural Equation Modeling

Objective. This study examined to what degree patient-centeredness—measured as an underlying ability of obstetrical nurses—influenced Medicaid patients’ satisfaction with care in hospital obstetrical units.Design. Multigroup structural equation modeling design, using three cross-sectional random samples (n=300each) from the 2003 Press Ganey National Inpatient Database.Setting. Self-administered mail surveys.Participants. 900 Medicaid recipients recently discharged from inpatient hospital obstetrical units across the United States.Methods. Multigroup structural equation modeling was used to test the goodness of fit between a hypothesized model based on the Primary Provider Theory and patients’ ratings of nurses.Results. The model fitted the data well, was stable across three random samples, and was sustained when compared to a competing model. The patient-centeredness of nurses significantly influenced overall patient satisfaction and explained 66% of its variability. When nurses’ patient-centeredness increased by one standard deviation, patients’ satisfaction increased by 0.80 standard deviation.Conclusion. This study offers a novel approach to the measurement of the patient-centeredness of nurses and a paradigm for increasing it and its influence on Medicaid patients’ satisfaction in hospital obstetrical units.

scholarly journals PEMODELAN STRUKTURAL DARI EMOSI POSITIF SEBAGAI PEMEDIASI TERHADAP PEMBELIAN TIDAK TERENCANA

2015 ◽  
Vol 4 (3) ◽  
pp. 104
Author(s):  
NI WAYAN ARNI YANITA ◽  
KETUT JAYANEGARA ◽  
I PUTU EKA N. KENCANA
Keyword(s):  
Structural Equation Modeling ◽  
Indirect Effect ◽  
Latent Variables ◽  
Structural Equation ◽  
Positive Emotions ◽  
Goodness Of Fit ◽  
Situational Factors ◽  
Equation Modeling ◽  
Impulse Buying ◽  
Mediation Models

Latent variables are variables that can not be observed directly. Latent variables can be observed with constituent indicators. One of the methods used to analyze the latent variables are Structural Equation Modeling (SEM). This research raised the case of impulse buying to be applied to the SEM method. Impulse buying influenced by the characteristics of the hypermarket, situational factors, the characteristics of the product, promotion and positive emotions. The purpose of this research was to determine the effect dari positive emotions as mediation to impulse buying.The results obtained indicate that positive emotions directly affect the impulse buying of 0.302, promotion directly affects the positive emotions of 0.367, and the promotion of indirect effect to impulse buying of 0.111. So positive emotions can mediate to impulse buying of 0.020. Goodness of fit mediation models not good with value 0.39.

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