Bibliographies thématiques / Structural equation modelling

Littérature scientifique sur le sujet « Structural equation modelling »

Auteur : Grafiati

Publié le 4 juin 2021

Mis à jour le 25 mai 2024

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Articles de revues sur le sujet "Structural equation modelling"

Tenenhaus, Michel. « Component-based Structural Equation Modelling ». Total Quality Management & ; Business Excellence 19, n^o 7-8 (août 2008) : 871–86. http://dx.doi.org/10.1080/14783360802159543.

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Kelloway, E. Kevin. « Structural equation modelling in perspective ». Journal of Organizational Behavior 16, n^o 3 (mai 1995) : 215–24. http://dx.doi.org/10.1002/job.4030160304.

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Chandrasekhar, S., et Chabi Sinha. « Modelling the Brand Equity Using Structural Equation Modelling ». Management Dynamics 8, n^o 2 (26 avril 2022) : 59–70. http://dx.doi.org/10.57198/2583-4932.1179.

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Dangi, H. K., Ashmeet Kaur et Juhi Jham. « Structural Equation Modelling : A Powerful Antibiotic ». Journal of Business Thought 10 (4 mars 2019) : 19–23. http://dx.doi.org/10.18311/jbt/2019/23452.

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Mitra, Pradip Kumar. « Structural Equation Modelling : A small review ». Journal of Development Research 9, n^o 3 (juillet 2016) : 34. http://dx.doi.org/10.54366/jdr.9.3.2016.34-38.

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Ziegel, Eric R., et R. Mueller. « Basic Principles of Structural Equation Modelling ». Technometrics 39, n^o 3 (août 1997) : 343. http://dx.doi.org/10.2307/1271158.

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MacFarlane, Don. « Structural equation modelling in developmental psychiatry ». British Journal of Psychiatry 193, n^o 6 (décembre 2008) : 509. http://dx.doi.org/10.1192/bjp.193.6.509.

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Smith, Philip T., Frank McKenna, Claire Pattison et Andrea Waylen. « Structural equation modelling of human judgement ». Thinking & ; Reasoning 7, n^o 1 (février 2001) : 51–68. http://dx.doi.org/10.1080/13546780042000037.

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Barrett, Paul. « Structural equation modelling : Adjudging model fit ». Personality and Individual Differences 42, n^o 5 (mai 2007) : 815–24. http://dx.doi.org/10.1016/j.paid.2006.09.018.

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Testa, Mark R. « Structural Equation Modelling in Hospitality Research ». Tourism and Hospitality Research 2, n^o 1 (avril 2000) : 67–74. http://dx.doi.org/10.1177/146735840000200110.

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Structural equation modelling (SEM) is a statistical procedure gaining increased attention in psychology, marketing and business research. As few studies in hospitality research utilise this cutting-edge method of modelling and testing linear relationships, this paper seeks to rationalise the implementation of its use. A conceptual and non-technical overview of the process is discussed, identifying the positive and negative aspects of the procedure. In addition, examples of SEM in practice in hospitality research are examined.

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Thèses sur le sujet "Structural equation modelling"

Yoo, Keunyoung. « Probabilistic SEM : an augmentation to classical Structural equation modelling ». Diss., University of Pretoria, 2018. http://hdl.handle.net/2263/66521.

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Structural equation modelling (SEM) is carried out with the aim of testing hypotheses on the model of the researcher in a quantitative way, using the sampled data. Although SEM has developed in many aspects over the past few decades, there are still numerous advances which can make SEM an even more powerful technique. We propose representing the nal theoretical SEM by a Bayesian Network (BN), which we would like to call a Probabilistic Structural Equation Model (PSEM). With the PSEM, we can take things a step further and conduct inference by explicitly entering evidence into the network and performing di erent types of inferences. Because the direction of the inference is not an issue, various scenarios can be simulated using the BN. The augmentation of SEM with BN provides signi cant contributions to the eld. Firstly, structural learning can mine data for additional causal information which is not necessarily clear when hypothesising causality from theory. Secondly, the inference ability of the BN provides not only insight as mentioned before, but acts as an interactive tool as the `what-if' analysis is dynamic.
Mini Dissertation (MCom)--University of Pretoria, 2018.
Statistics
MCom
Unrestricted

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McKenzie, Kirsten. « Exploring first year academic success through structural equation modelling ». Thesis, Queensland University of Technology, 2002. https://eprints.qut.edu.au/36788/2/36788_Digitised%20Thesis.pdf.

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Vargas, Sepúlveda Mauricio. « Structural equation modelling application : profiling and analyzing students' university scores ». Tesis, Universidad de Chile, 2015. http://repositorio.uchile.cl/handle/2250/135274.

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Seminario para optar al grado de Ingeniero Comercial, Mención Administración
This work analyses chilean university students performance in different courses. These students belong to different major programs imparted at Universidad de Chile: Accounting, Business Administration, Economics and Information Systems. The analyzed courses are those they share under the same course syllabus and examination and also they are mixed together without distinction of their respective programs in those courses. The provided dataset for this work considers the period 2002-2013. The cornerstone of this study is to determine if the course performance can be analyzed under a satisfactory factorial structure. For this purpose I used Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) which is a part of Structural Equation Modeling (SEM). Cronbach’s Alpha and Vuong Test are used for cross validation and to choose the best model from data. This work uses advanced statistical tools and Psychometric Theory developments are considered as theoretical pillars of this study. Altogether with this pdf file, the interested reader may find the datasets and both the LATEX and R files I’ve created during this work in the next URL: http://github.com/pachamaltese/thesis. My github repo includes all the diagrams and the thesis template that I’ve designed according to my university’s rules.

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Hassan, Louise May. « Hierarchical stepwise structural equation modelling : a methodological contribution for combining theories ». Thesis, Glasgow Caledonian University, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.404635.

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Tseng, Wen-Ta. « Motivation, self-regulation and vocabulary acquisition : a structural equation modelling analysis ». Thesis, University of Nottingham, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.430477.

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Caldarola, Bernardo. « Poverty traps in Southern rural Mozambique : a structural equation modelling approach ». Master's thesis, Instituto Superior de Economia e Gestão, 2016. http://hdl.handle.net/10400.5/12861.

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Mestrado em Desenvolvimento e Cooperação Internacional
Este trabalho visa analisar o contexto de economia rural em três distritos da região Sul de Mozambique, para demonstrar a existência de mecanismos "aprisionadores" que detêm as famílias camponesas numa condição de pobreza. Todas as variáveis tomadas em conta para o estudo resultam de uma base de dados autoproduzida que inclui informação sobre a subsistência no contexto rural e o sector agrícola. Este trabalho utiliza a abordagem dos modelos de equações estruturais (SEM) para detectar as possíveis não-linearidades no processo de criação de riqueza, em particular a través da análise da saúde, do contexto institucional e de mercado, e da segurança alimentar em relação à riqueza das famílias. Recorrendo aos conceitos de complexidade, multidimensionalidade e causação cumulativa, procura-se demonstrar a existência de uma "armadilha da pobreza" a partir da análise das diversas dinâmicas relacionadas com a relação que existe entre segurança alimentar e bem-estar das famílias inquiridas. A metodologia adotada neste trabalho constitui uma alternativa aos testes tradicionalmente utilizados na investigação sobre as armadilhas da pobreza, pois inclui um numero maior de factores na analise da pobreza persistente. Em conclusão, os resultados da estimação do modelo fornecem algumas recomendações em termos de politicas de combate contra a pobreza, de acordo com as características especificas da zona.
This article analyses the rural economy of three districts in southern Mozambique, proving the existence of a lock-in device that keeps small-scale farmers and their households into poverty. All variables taken into account result from an original survey-based dataset which includes socio-economic information about rural livelihoods and the agricultural sector. A Structural Equation Modelling approach is adopted to detect non-linearity in wealth creation - in particular by analysing health, market/institutional environment and food security in relation to an asset-based measure of wealth. Drawing upon the concepts of complexity, multidimensionality and cumulative causation, this work proves the existence of a poverty trap by analysing the varying dynamics related to the relationship that exists between food security and wealth. The methodology adopted in this work represents an alternative to the traditional tests usually applied for the detection of poverty traps, including a wider number of factors in the study of persistent poverty; finally, it provides some useful policy recommendations regarding the struggle against poverty in this area.
N/A

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Cunliffe, Jack. « Offending risk factors and area : an investigation using structural equation modelling ». Thesis, London School of Economics and Political Science (University of London), 2015. http://etheses.lse.ac.uk/3257/.

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This thesis has two main aims. The first is substantive: to investigate whether and how an individual’s perceptions of their area act as risk factors for offending. The second is methodological: to demonstrate that theoretically-informed structural equation modelling can make best use of existing and often under-utilised datasets, particularly cross-national studies such as those typically conducted by large-scale organisations or governments. Using the United Kingdom Offending, Crime and Justice Survey (OCJS) conducted between 2003 and 2006, and taking a range of questions on individual perceptions, family circumstance, self-reported offending and variables relating to the area in which the respondent lives, the work reviews previous criminological measurement constructs of well-known risk factors (from both an analytical and theoretical perspective) and once these are defined moves on to examine self-report offending using structural equation modelling. Findings are predominantly consistent with previous work and show that individual criminogenic propensities matter most, but also that a complex interrelationship of area perceptions operate in conflicting directions. Once this is accounted for, living in an area with higher disorder seems to increase self-report offending, with part of the relationship explained by perceptions of lower collective efficacy. However, this relationship seems to operate only at one time point and when looking longitudinally it appears that it is the family situation that takes precedence. This leads in turn to mixed policy implications. In the short-term, it appears that interventions to address perception of area would be most successful to combat offending behaviour but over the longer term addressing the family situation would be more appropriate. Implications for data collection processes and analytical approaches to existing data are centred on the simple analytical framework that pays equal attention to the set of questions: 1) What can be measured? 2) Can these measures be structured? 3) What are the results?

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Neoh, Jun. « Application of meta-analysis, multidimensional scaling, structural equation modelling, and multilevel modelling in analysing carpooling behaviour ». Thesis, University of Southampton, 2016. https://eprints.soton.ac.uk/395306/.

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Alzahrani, Ahmed Ibrahim. « Web-based e-government services acceptance for G2C : a structural equation modelling approach ». Thesis, De Montfort University, 2011. http://hdl.handle.net/2086/5181.

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E-Government is the use of information technology particularly web applications to deliver convenient services for citizens, business and government. Governments worldwide spend billions of their budgets in order to deliver convenient electronic services to their citizens. There are two important points; government offers online services, and citizens consume these services. In order to maximize the benefits of these projects and to avoid possible failures, the gap between these points should be addressed. Yet there are few empirical studies that have covered the relevant issues of adoption from the citizen perspective in developing countries. This research study investigates citizens’ acceptance of e-government services in the context of Saudi Arabia. It posits an integrated model of the key elements that influence citizens’ adoption of e-government. The framework includes a combination of attitudinal, social, control and trust factors as well as the influence of gender. The model is validated by surveying 533 citizens and utilising the structural equation modeling technique for data analysis. Findings show that both measurement and structural models exhibit good model fit to data. The study shows that all constructs satisfy the criteria of constructs reliability and convergent and discriminant validity. The paths estimations show that of the sixteen designed casual relationships, eleven paths relationships were found to be significant while the other five paths remained unsupported.

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Nuthethi, Rishita Optometry &amp Vision Science Faculty of Science UNSW. « Structural equation modelling and its application to quality of life of visually impaired people ». Awarded by:University of New South Wales. Optometry & ; Vision Science, 2008. http://handle.unsw.edu.au/1959.4/44537.

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The main objective of the thesis was to construct a model of r:lationships among perceived visual ability (VF), quality of life (QOL) and visual acuity (VA) using the structural equation modeling (SEM) technique in an older, visually impaired population of India. The World Health Organization QOL questionnaire, adopted as a QOL questionnaire, and a 16-item visual function questionnaire (VFQ) were administered to adults in the population-based Andhra Pradesh Eye Disease Study prior to their detailed eye examination. Participants aged 40 years and older (n=3,702), who underwent an interview by trained professionals, were included in this study. A total of 1,333 visually impaired subjects (presenting VA < 6/18) responded to both questionnaires. The VFQ and QOL questionnaires were evaluated using Rasch analysis. The general linear model analysis (GLM) was performed to identify the factors associated with the measures of perceived visual ability and QOL. The direct and indirect relationships between VA, perceived visual ability and QOL were established using the SEM after adjusting for socio-demographic factors identified to be significant in GLM. The mean age of the visually impaired participants was 60.5 years; 753 (56%) were female. There were 760 visually impaired people with cataract in at least one eye, 524 with uncorrected refractive error, 84 with retinal disease, 41 with glaucoma and 60 with corneal disease. The VFQ and QOL measures were found to be valid and unidimensional for those with retinal disease, glaucoma, corneal disease and those who are blind due to cataract or any other cause. In QOL questionnaire the item that required the most ability was "chance to acquire new skills" and the item that required the least ability was "dressing" for the sample with retinal disease, glaucoma, corneal disease and cataract. In the VFQ, the items that required the most visual ability were "recognizing small objects" and "recognizing people across the street". The items that required least visual ability were "reaching an object that is farther or closer than you thought" and "identifying colors". Perceived visual ability to perform the functional vision activities mediated the relationship between VA and QOL, a new diagram for the International Classification of Functioning (ICF), however, the percentage of change mediated through perceived functional ability varied for different eye diseases. The total change that was mediated through perceived functional ability was 100%, 100%, 52%, 52% and 63% for people with retinal disease, glaucoma, corneal disease and those who are blind due to cataract or any cause of disease, respectively. Decreased QOL and perceived visual ability was associated with the presence of glaucoma or corneal disease independent of VA and with cataract and retinal disease as a function of VA. Perceived visual ability to perfol111 the functional vision activities mediates the relationship between VA and QOL. Improving the perceived visual ability would improve the QOL of low vision persons. Further longitudinal studies on the impact of therapy and rehabilitation for glaucoma, corneal disease and retinal disease on QOL and VF are needed.

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Livres sur le sujet "Structural equation modelling"

Thakkar, Jitesh J. Structural Equation Modelling. Singapore : Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3793-6.

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Jak, Suzanne. Meta-Analytic Structural Equation Modelling. Cham : Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-27174-3.

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Bynner, John. Modelling childhood antecedents of political cynicism using structural equation modelling. London : Social Statistics Research Unit, City University, 1996.

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P, Odekerken M. E., Schmeets J. J. G et Pol, F. J. R. van de., dir. Developments and applications in structural equation modelli ng : Proceedings of the twelfth meeting of the "Working group structural equation modelling" ("A G Strukturgleichungsmodelle"). Amsterdam : Sociometric Research Foundation, 1991.

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Bhattacharya, Joysankar. Women empowerment as multidimensional capability enhancement : An application of structural-equation-modelling. Kolkata : Institute of Development Studies, 2012.

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Jöreskog, K. G. LISREL 8 : Structural equation modeling with the SIMPLIS command language. Hillsdale, NJ : Scientific Software International, 1993.

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Hanna, Jim. Assessing consumer preference for local independent retailers : An application of structural equation modelling (SEM). (s.l : The Author), 2000.

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Jöreskog, K. G. LISREL 8 : Structural equation modeling with the SIMPLIS command language. Chicago, Ill : Scientific Software International, 1993.

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O'Loughlin, Christina. Evaluation of measurement quality in the assessment of health related issues using structural equation modelling techniques. [s.l : The Author], 2000.

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Angell, Rob. Learn to Do Structural Equation Modelling (SEM) in SPSS AMOS With Data From the International Sponsorship Study (2016). 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom : SAGE Publications, Ltd., 2019. http://dx.doi.org/10.4135/9781526469632.

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Chapitres de livres sur le sujet "Structural equation modelling"

Yang, Yanyun. « Structural equation modelling ». Dans Advanced Research Methods for Applied Psychology, 246–58. Abingdon, Oxon ; New York, NY : Routledge, [2018] : Routledge, 2018. http://dx.doi.org/10.4324/9781315517971-24.

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Thakkar, Jitesh J. « Introduction to Structural Equation Modelling ». Dans Structural Equation Modelling, 1–11. Singapore : Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3793-6_1.

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Thakkar, Jitesh J. « Technical Aspects of SEM ». Dans Structural Equation Modelling, 13–27. Singapore : Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3793-6_2.

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Thakkar, Jitesh J. « Procedural Steps in Structural Equation Modelling ». Dans Structural Equation Modelling, 29–34. Singapore : Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3793-6_3.

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Thakkar, Jitesh J. « Applications of Structural Equation Modelling with AMOS 21, IBM SPSS ». Dans Structural Equation Modelling, 35–89. Singapore : Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3793-6_4.

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Thakkar, Jitesh J. « Applications of Structural Equation Modelling with R ». Dans Structural Equation Modelling, 91–99. Singapore : Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3793-6_5.

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Thakkar, Jitesh J. « Applications of SEM and FAQs ». Dans Structural Equation Modelling, 101–12. Singapore : Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3793-6_6.

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Woodrow, Lindy. « Writing about Structural Equation Modelling ». Dans Writing about Quantitative Research in Applied Linguistics, 122–34. London : Palgrave Macmillan UK, 2014. http://dx.doi.org/10.1057/9780230369955_11.

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Verma, J. P., et Priyam Verma. « Overview of Structural Equation Modelling ». Dans Synthesis Lectures on Mathematics & ; Statistics, 1–12. Cham : Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-32673-8_1.

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Schuhen, Michael, et Susanne Schürkmann. « Construct Validity with Structural Equation Modelling ». Dans International Handbook of Financial Literacy, 383–96. Singapore : Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0360-8_26.

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Actes de conférences sur le sujet "Structural equation modelling"

Li, Rita, Li Herru, Beiqi Tang et Fung Darren. « Building safety index : Structural Equation Modelling approach ». Dans 24th Annual European Real Estate Society Conference. European Real Estate Society, 2017. http://dx.doi.org/10.15396/eres2017_358.

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Tan, Wei Chin Jess, et Hian Chye Koh. « Applying Structural Equation Modelling in Education Research ». Dans 2023 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE). IEEE, 2023. http://dx.doi.org/10.1109/tale56641.2023.10398315.

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de Waal, Alta, et Keunyoung Yoo. « Latent Variable Bayesian Networks Constructed Using Structural Equation Modelling ». Dans 2018 International Conference on Information Fusion (FUSION). IEEE, 2018. http://dx.doi.org/10.23919/icif.2018.8455240.

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« Analysis of South Korean basin hydrologic cycle using structural equation model ». Dans 25th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, 2023. http://dx.doi.org/10.36334/modsim.2023.song333.

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Bulut, Ayse, et Nazime Tuncay. « SOCIAL MEDIA ADDICTION AND SLEEP PROBLEM : A STRUCTURAL EQUATION MODELLING ». Dans eLSE 2020. University Publishing House, 2020. http://dx.doi.org/10.12753/2066-026x-20-060.

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Sleep disorder is a condition that may be very damaging and may be related to poor mental health and low academic performance. The causes of sleep disorder had been interest of many researches for decades, however not a realistic solution could be found until today. Do new scientific improvements and new software do good to our dentistry students or does it do bad? Should we put a restriction to Social Media usage like WhatsApp group messages and night-time Smartphone use? Does Social Media effect students sleep and their academic performance? To understand this we had to deliver a research study in Cyprus Health and Social Sciences University dentistry students. Although there are lots of research studies about sleep disorder and social media, there were not any studies delivered in Cyprus. WhatsApp groups are widely used in Cyprus Health and Sciences University for academic purposes like information sharing and social life communications. Sleep performance of students is closely related to their success. A detailed literature review is done about Sleep Disorder and Social Media Effects on Sleep Disorder. A Good sleep is important for all students and may be it is more important for dentistry students who have a very intense course schedule than the other students. Sleep Disorder Questionarie and Social Media Addiction Questionnaire is used to get information about students Sleep- Social Media Behaviors. In total 150 students have attained to this research study and there were interesting differences according to students demographic properties. Recommendations to improve quality of sleep and to prevent social media addiction is given by the authors.

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Zhao, Yanhua. « Research on Purchase Intentions of Residential Product Based on Structural Equation Model ». Dans 2008 International Workshop on Modelling, Simulation and Optimization. IEEE, 2008. http://dx.doi.org/10.1109/wmso.2008.45.

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Nair, D. J., N. Saxena et V. V. Dixit. « Evaluating the Perception Index for Cyclists’ Safety Using Structural Equation Modelling ». Dans International Conference on Transportation and Development 2016. Reston, VA : American Society of Civil Engineers, 2016. http://dx.doi.org/10.1061/9780784479926.098.

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Pujianti, F., I. Novianty et D. Suhartanto. « Predicting Sustainability in The Banking Industry : A Structural Equation Modelling Approach ». Dans International Seminar of Science and Applied Technology (ISSAT 2020). Paris, France : Atlantis Press, 2020. http://dx.doi.org/10.2991/aer.k.201221.096.

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Ajayi, Saheed O. « Optimal strategies for construction waste mitigation : A structural equation modelling approach ». Dans TOWARD ADAPTIVE RESEARCH AND TECHNOLOGY DEVELOPMENT FOR FUTURE LIFE. AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0114114.

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Rashmi, Manish Kumar, Abhishek Joshi, Suhasini Reddy. T, Ali Hussein et Malik Bader Alazzam. « Technical Analysis of Performance of sentimental behaviours using Structural Equation Modelling ». Dans 2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE). IEEE, 2023. http://dx.doi.org/10.1109/icacite57410.2023.10182667.

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Rapports d'organisations sur le sujet "Structural equation modelling"

Dormann, Christian. Introduction to Continuous Time Structural Equation Modeling (CTSEM). Instats Inc., 2023. http://dx.doi.org/10.61700/kwigtxevhohxk469.

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This seminar introduces the use of Continuous Time Structural Equation Modeling (CTSEM) to study phenomena over time in the social and health sciences. Day 1 topics include the required conceptual background, mathematical foundations, as well as examples to illustrate the concepts. On Day 2, the R package [b]ctsem [/b]is introduced, with hands-on coverage of topics including data preparation, model setup, parameter estimation, and interpretation of results. Day 3 topics include random intercept modelling (aka., within-person analysis), moderator analysis, and an outlook to Continuous Time Meta-Analysis (CoTiMA) using results from multiple studies. An official Instats certificate of completion is provided at the conclusion of the seminar. The seminar offers 2 ECTS Equivalent points for European PhD students.

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Dormann, Christian. Introduction to Continuous Time Structural Equation Modeling (CTSEM) + 1 Free Seminar. Instats Inc., 2022. http://dx.doi.org/10.61700/am2g78fjl1gx5469.

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This seminar introduces the use of Continuous Time Structural Equation Modeling (CTSEM) to study phenomena over time in the social and health sciences. Day 1 topics include the required conceptual background, mathematical foundations, as well as examples to illustrate the concepts. On Day 2, the R package [b]ctsem [/b]is introduced, with hands-on coverage of topics including data preparation, model setup, parameter estimation, and interpretation of results. Day 3 topics include random intercept modelling (aka., within-person analysis), moderator analysis, and an outlook to Continuous Time Meta-Analysis (CoTiMA) using results from multiple studies. To frame the seminar content, a free background seminar is provided when enrolling: Longitudinal SEM in R. An official Instats certificate of completion is provided at the conclusion of the seminar. The seminar offers 2 ECTS Equivalent points for European PhD students.

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Diba, Dil Samina, Ninad Gore et Srinivas Pulugurtha. Autonomous Shuttle Implementation and Best Practices. Mineta Transportation Institute, décembre 2023. http://dx.doi.org/10.31979/mti.2023.2321.

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When, where, and how autonomous shuttles are deployed can have significant safety, economic, and policy impacts on their operation and performance. This research analyzes data related to 120 existing deployments of autonomous shuttles, looking at safety, operational, economic, and policy-related issues. Analysis shows that autonomous shuttles would be an excellent supplement to public transportation. However, improvements to the vehicle and the infrastructure are needed before any permanent deployment. The study also analyzes the perceptions of practitioners, industry experts, and transportation system users toward autonomous shuttles. Principal Component Analysis (PCA) and Multiple Input Multiple Cause Structural Equation Modelling (SEM) approaches were adopted to analyze the perception data. The results from the PCA highlighted critical barriers to autonomous shuttle implementation, including underutilization measures, safety concerns, seating arrangements, reliability, data security, operational aspects, sensor technology, and lane use. The results from the SEM revealed that users’ willingness to use autonomous shuttles is influenced by their perceived safety, comfort, trust in autonomous shuttles, familiarity with autonomous shuttles, household income, age, and frequency of transit usage. A set of recommended best practices for deploying autonomous shuttles is proposed based on the insights from multiple case studies and the perceptions of practitioners and industry experts.

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Rouhi, A. Final report for symmetric truncations of the shallow water equations and modelling of coherent structures in a boundary layer. Office of Scientific and Technical Information (OSTI), décembre 1996. http://dx.doi.org/10.2172/573288.

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