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Książki na temat „Structural equation modelling”

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Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 25 maja 2024

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1

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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2

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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4

P, Odekerken M. E., Schmeets J. J. G i Pol, F. J. R. van de., red. 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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6

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

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7

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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8

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

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9

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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10

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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Alves Ribeiro Correia, Pedro. Using Structural Equation Modelling and Clustering to Research Users’ and Employees’ views of the Portuguese Ministry of Justice. 1 Oliver’s Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications Inc., 2023. http://dx.doi.org/10.4135/9781529628326.

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12

Schumacker, Randall E. A beginner's guide to structural equation modeling. Mahwah, N.J: L. Erlbaum Associates, 1996.

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13

Schumacker, Randall E. A beginner's guide to structural equation modeling. Wyd. 2. Mahwah, N.J: Lawrence Erlbaum Associates, 2004.

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14

Loehlin, John C. Latent variable models: An introduction to factor, path, and structural equation analysis. Wyd. 4. Mahwah, N.J: L. Erlbaum Associates, 2004.

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15

Conference on Multi-scale and High-contrast PDE: from Modelling, to Mathematical Analysis, to Inversion (2011 Oxford, England). Multi-scale and high-contrast PDE: From modelling, to mathematical analysis, to inversion : Conference on Multi-scale and High-contrast PDE:from Modelling, to Mathematical Analysis, to Inversion, June 28-July 1, 2011, University of Oxford, United Kingdom. Redaktorzy Ammari Habib, Capdeboscq Yves 1971- i Kang Hyeonbae. Providence, R.I: American Mathematical Society, 2010.

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16

Loehlin, John C. Latent variable models: An introduction to factor, path, and structural analysis. Wyd. 3. Mahwah, N.J: Lawrence Erlbaum, 1998.

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Loehlin, John C. Latent variable models: An introduction to factor, path, and structural analysis. Wyd. 2. Hillsdale, N.J: Lawrence Erlbaum Associates, 1992.

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18

Loehlin, John C. Latent variable models: An introduction to factor, path, and structural analysis. Hillsdale, N.J: L. Erlbaum Associates, 1987.

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19

Jak, Suzanne. Meta-Analytic Structural Equation Modelling. Springer, 2015.

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Jak, Suzanne. Meta-Analytic Structural Equation Modelling. Springer London, Limited, 2015.

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21

Thakkar, Jitesh J. Structural Equation Modelling: Application for Research and Practice. Springer, 2020.

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22

Thakkar, Jitesh J. Structural Equation Modelling: Application for Research and Practice. Springer Singapore Pte. Limited, 2021.

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23

Blunch, Niels. Introduction to Structural Equation Modelling Using SPSS and AMOS. Sage Publications Ltd, 2008.

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24

Blunch, Niels. Introduction to Structural Equation Modelling Using SPSS and AMOS. Sage Publications Ltd, 2008.

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25

Blunch, Niels. Introduction to Structural Equation Modelling Using SPSS and Amos. SAGE Publications, Incorporated, 2008.

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26

Hemsworth, David. Modelling using ordinal data: The use of dual scaling in structural equation modelling. 2004.

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27

Hoyle, Rick H. Applications of structural equation modelling in clinical and health psychology research. Oxford University Press, 2015. http://dx.doi.org/10.1093/med:psych/9780198527565.003.0020.

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This chapter discusses applications of structural equation modelling (SEM, or causal modelling) in clinical and health psychology research. It outlines path diagrams, measurement models, structural models, the inclusion of latent variables, validity (factorial and construct), and measurement invariance. Structural hypotheses are also explored, along with caveats for the use of SEM.

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28

Mehmetoglu, Mehmet, i Sergio Venturini. Structural Equation Modelling with Partial Least Squares Using Stata and R. Taylor & Francis Group, 2021.

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Mehmetoglu, Mehmet, i Sergio Venturini. Structural Equation Modelling with Partial Least Squares Using Stata and R. Taylor & Francis Group, 2021.

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30

Mehmetoglu, Mehmet, i Sergio Venturini. Structural Equation Modelling with Partial Least Squares Using Stata and R. Taylor & Francis Group, 2021.

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31

Mehmetoglu, Mehmet, i Sergio Venturini. Structural Equation Modelling with Partial Least Squares Using Stata and R. Taylor & Francis Group, 2021.

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32

Lee, Sik-Yum. Structural Equation Modelling: A Bayesian Approach (Wiley Series in Probability and Statistics). Wiley, 2007.

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Metacognitive and Cognitive Strategy Use in Reading Comprehension: A Structural Equation Modelling Approach. Springer Singapore Pte. Limited, 2019.

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34

Zhang, Limei. Metacognitive and Cognitive Strategy Use in Reading Comprehension: A Structural Equation Modelling Approach. Springer, 2017.

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35

Joreskog, Karl G., i Dag Sorbom. Lisrel 8 : Structural Equation Modeling With the Simplis Command Language. Lawrence Erlbaum Associates, 1993.

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36

(Editor), Kees van Montfort, Johan Oud (Editor) i Albert Satorra (Editor), red. Recent Developments on Structural Equation Models: Theory and Applications (Mathematical Modelling: Theory and Applications). Springer, 2004.

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37

M, Sardar. Digitalisation of Supply Chain Management and Firm Performance: Structural Equation Modelling and Empirical Findings. Nova Science Publishers, Incorporated, 2020.

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M, Sardar. Digitalisation of Supply Chain Management and Firm Performance: Structural Equation Modelling and Empirical Findings. Nova Science Publishers, Incorporated, 2019.

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39

Joreskog, Karl G., i Dag Sorbom. Lisrel 8: Structural Equation Modeling With the Simplis Command Language. Lawrence Erlbaum Associates, 1993.

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40

Ramlall, Indranarain. Applied Structural Equation Modelling for Researchers and Practitioners: Using R and Stata for Behavioural Research. Emerald Publishing Limited, 2016.

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41

Ramlall, Indranarian. Applied Structural Equation Modelling for Researchers and Practitioners: Using R and Stata for Behavioral Research. Emerald Publishing Limited, 2016.

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42

Boateng, Sheena, i Richard Boateng. Structural Equation Modelling Made Easy for Business and Social Science Research Using SPSS and Amos. Independently Published, 2018.

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43

Rabe-Hesketh, Sophia, i Anders Skrondal. Generalized Latent Variable Modeling: Multilevel, Longitudinal, and Structural Equation Models. Chapman & Hall/CRC, 2004.

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44

Kessels, Roselinde, i Guido Erreygers. A unified structural equation modelling approach for the decomposition of rank-dependent indicators of socioeconomic inequality of health. UNU-WIDER, 2015. http://dx.doi.org/10.35188/unu-wider/2015/902-2.

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45

Eriksson, Olle, Anders Bergman, Lars Bergqvist i Johan Hellsvik. Density Functional Theory. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198788669.003.0001.

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Density functional theory (DFT) has established itself as a very capable platform for modelling from first principles electronic, optical, mechanical and structural properties of materials. Starting out from the Dirac equation for the many-body system of electrons and nuclei, an effective theory has been developed allowing for materials specific and parameter free simulations of non-magnetic and magnetic solid matter. In this Chapter an introduction will be given to DFT, the Hohenberg-Kohn theorems, the Kohn-Sham equation, and the formalism for how to deal with non-collinear magnetism.

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46

Adamson, Gary, i Brendan Bunting. Some statistical and graphical strategies for exploring the effect of interventions in health research. Oxford University Press, 2015. http://dx.doi.org/10.1093/med:psych/9780198527565.003.0021.

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This chapter explores statistical and graphical strategies for exploring the effect of interventions in health research and presents a brief overview of some common and some not so common methods for assessing data from interventions and have pointed to some associated advantages and disadvantages. It discusses gain scores, analysis of variance models, structural equation modelling, and the latent growth model.

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47

Olejnik, Iwona, red. Qualitative and quantitative methods in sustainable development. Wydawnictwo Uniwersytetu Ekonomicznego w Poznaniu, 2021. http://dx.doi.org/10.18559/978-83-8211-072-2.

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Systematic research and comprehensive analyses allow to monitor the implementation of the sustainable development goals. Obviously, when you are interested in the selected issue of sustainable development, it is worth using data from the secondary sources in the first place. This e-book presents a few selected methods that will allow you to answer the questions: how to gather data and how to analyse them? Among the data collection methods presented in this book, we have chosen both: qualitative, in particular focus group interview, and quantitative—based on a questionnaire. In terms of data analysis methods, we present three methods: factor analysis, structural equation modelling and data envelopment analysis. The examples presented in this book relate to sustainable development, for example: sustainable consumption, ecological culture, better nutrition, agricultural development and many more. The book consists of five chapters. Chapter 1 “Qualitative methods” presents the issues concerning the methodology of qualitative research, designing a focus group interview, conducting a focus group interview and analysis of qualitative data using the CAQDAS programs. The main goal of Chapter 2 titled “Quantitative methods” is to exhibit the basics of survey research that can be used in analyses of sustainable development. In particular, this part presents the measurement levels, questionnaire design, population and sample, and the ways of presenting the results of quantitative research. Chapter 3 “Factor analysis in sustainable development research” describes the basic theoretical aspects of factor analysis. The second part of this chapter presents an example of the use of this method in research on sustainable consumption. The last part of this chapter presents case study of the use of factor analysis in research on managers’ ethics in retail industry. Chapter 4 titled “Structural equation modelling in sustainable development research” is dedicated to the structural equation modeling methods applied to solve sustainable development research problems. A structural equation model is an abstraction of reality, and the researcher's job is to build a model that approximates that reality as closely as possible. And the aim of Chapter 5 “Data envelopment analysis methods in sustainable agricultural development research” is to determine the relative technical efficiency of representative agricultural farms from the individual European Union countries.

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Parker, Clare. Testing an existing customer satisfaction model using structual equation modelling. 1997.

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Panasenko, G. Multi-scale Modelling for Structures and Composites. Springer, 2010.

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Panasenko, G. Multi-scale Modelling for Structures and Composites. Springer, 2008.

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