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Books on the topic 'Latent variables model'

Author: Grafiati

Published: 4 June 2021

Last updated: 8 February 2022

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1

Heinen, Ton. Discrete latent variable models. Tilburg University Press, 1993.

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2

Loglinear models with latent variables. Sage, 1993.

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3

Hagenaars, Jacques. Loglinear models with Latent Variables. SAGE Publications, Inc., 1993. http://dx.doi.org/10.4135/9781412984850.

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4

Semialgebraic statistics and latent tree models. CRC Press, Taylor & Francis Group, 2016.

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5

Dunson, David B., ed. Random Effect and Latent Variable Model Selection. Springer New York, 2008. http://dx.doi.org/10.1007/978-0-387-76721-5.

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6

Bartholomew, David, Martin Knott, and Irini Moustaki. Latent Variable Models and Factor Analysis. John Wiley & Sons, Ltd, 2011. http://dx.doi.org/10.1002/9781119970583.

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7

Bartholomew, David J. Latent variable models and factor analysis. 2nd ed. Arnold, 1999.

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8

Bartholomew, David J. Latent variable models and factor analysis. C. Griffin, 1987.

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9

1965-, Curran Patrick J., ed. Latent curve models: A structural equation perspective. John Wiley & Sons, 2005.

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10

Bollen, Kenneth A. Latent curve models: A structural equation perspective. Wiley Interscience, 2005.

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11

Bollen, Kenneth A. Latent curve models: A structural equation perspective. Wiley-Interscience, 2006.

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12

Bartholomew, David J. Latent variable models and factor analysis: A unified approach. 3rd ed. Wiley, 2011.

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13

Muthen, Linda K. Mplus: Statistical analysis with latent variables : user's guide. 4th ed. Muthén & Muthén, 2007.

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14

Current topics in the theory and application of latent variable models. Psychology Press, 2013.

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15

Latent variable models: An introduction to factor, path, and structural analysis. 3rd ed. Lawrence Erlbaum, 1998.

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16

Loehlin, John C. Latent variable models: An introduction to factor, path, and structural analysis. 2nd ed. Lawrence Erlbaum Associates, 1992.

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17

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

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18

Latent variable models: An introduction to factor, path, and structural equation analysis. 4th ed. L. Erlbaum Associates, 2004.

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19

Vermunt, Jeroen K. Log-linear event history analysis: A general approach with missing data, latent variables, and unobserved heterogeneity. Tilburg University Press, 1996.

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20

Dijkstra, Taeke Klaas. Latent variables in linear stochastic models: Reflections on "maximum likelihood" and "partial least squares" methods. 2nd ed. Sociometric Research Foundation, 1985.

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21

Ang, Andrew. A no-arbitrage vector autoregression of term structure dynamics with macroeconomic and latent variables. National Bureau of Economic Research, 2001.

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22

Hillmer, Matthias. Kausalanalyse makroökonomischer Zusammenhänge mit latenten Variablen: Mit einer empirischen Untersuchung des Transmissionsmechanismus monetärer Impulse. Physica-Verlag, 1993.

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23

Harris, Jeffrey E. Impact of "seguro popular" on prenatal visits in Mexico, 2002-2005: Latent class model of count data with a discrete endogenous variable. National Bureau of Economic Research, 2009.

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24

Heckman, James J. Simple estimators for treatment parameters in a latent variable framework with an application to estimating the returns to schooling. National Bureau of Economic Research, 2000.

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25

Anders, Skrondal, ed. Multilevel and longitudinal modeling using Stata. 3rd ed. Stata Press Publication, 2012.

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26

Babeshko, Lyudmila, Mihail Bich, and Irina Orlova. Econometrics and econometric modeling. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1141216.

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The textbook covers a wide range of issues related to econometric modeling. Regression models are the core of econometric modeling, so the issues of their evaluation, testing of assumptions, adjustment and verification are given a significant place. Various aspects of multiple regression models are included: multicollinearity, dummy variables, and lag structure of variables. Methods of linearization and estimation of nonlinear models are considered. An apparatus for evaluating systems of simultaneous and apparently unrelated equations is presented. Attention is paid to time series models. Deta

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27

Koldaev, Viktor. Theoretical and methodological aspects of the use of information technologies in education. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1014651.

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The article summarizes the experience of implementing a personality-oriented approach to the formation of a structural and content model of the educational process at the university. The results of the introduction of information technologies and their services in the field of education are presented, as well as the impact of computerization on the quality of education in the framework of the modern educational paradigm. The priority directions of innovative educational strategies of the university are identified and a graph model of the individual educational route of the student is proposed

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28

Babeshko, Lyudmila, and Irina Orlova. Econometrics and econometric modeling in Excel and R. INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1079837.

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The textbook includes topics of modern econometrics, often used in economic research. Some aspects of multiple regression models related to the problem of multicollinearity and models with a discrete dependent variable are considered, including methods for their estimation, analysis, and application. A significant place is given to the analysis of models of one-dimensional and multidimensional time series. Modern ideas about the deterministic and stochastic nature of the trend are considered. Methods of statistical identification of the trend type are studied. Attention is paid to the evaluati

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29

Dadyan, Eduard. Modern programming technologies. The C#language. Volume 1. For novice users. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1196552.

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Volume 1 of the textbook is addressed to novice users who want to learn the popular object-oriented programming language C#. The tutorial provides complete information about the C# language and platform .NET. Basic data types, variables, functions, and arrays are considered. Working with dates and enumerations is shown. The elements and constructs of the language are described: classes, interfaces, assemblies, manifests, namespaces, collections, generalizations, delegates, events, etc. It provides information about Windows processes and threads, as well as examples of organizing work in multit

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30

B, Dunson David, ed. Random effect and latent variable model selection. Springer, 2008.

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31

Jackman, Simon. Measurement. Edited by Janet M. Box-Steffensmeier, Henry E. Brady, and David Collier. Oxford University Press, 2009. http://dx.doi.org/10.1093/oxfordhb/9780199286546.003.0006.

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This article shows that the words ‘behavioural’ and ‘behaviour’ turn out to be better measures as judged by tests of criterion and convergent validity. It specifically discusses measurement problems. Further, it pertains to statistical models that link latent variables and their observed indicators as measurement models. The success of measurement — the quality of the inferences provided by a measurement model — is usually assessed with reference to two key concepts: validity and reliability. The distinct uses of measures of latent variables are reported. The article then deals with the costs

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32

Bollen, Kenneth A., Sophia Rabe‐Hesketh, and Anders Skrondal. Structural Equation Models. Edited by Janet M. Box-Steffensmeier, Henry E. Brady, and David Collier. Oxford University Press, 2009. http://dx.doi.org/10.1093/oxfordhb/9780199286546.003.0018.

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This article explains the use of factor analysis types of models to develop measures of latent concepts which were then combined with causal models of the underlying latent concepts. In particular, it offers an overview of the classic structural equation models (SEMs) when the latent and observed variables are continuous. Then it looks at more recent developments that include categorical, count, and other noncontinuous variables as well as multilevel structural equation models. The model specification, assumptions, and notation are covered. This is followed by addressing implied moments, ident

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33

J, Aigner Dennis, and Deistler Manfred, eds. Latent variables models. North-Holland, 1989.

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34

Loehlin, John C. Latent Variable Models. Psychology Press, 2004. http://dx.doi.org/10.4324/9781410609823.

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35

Latent Variable Models. Routledge, 2016. http://dx.doi.org/10.4324/9781315643199.

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36

A, Marcoulides George, and Moustaki Irini, eds. Latent variable and latent structure models. Lawrence Earlbaum Publishers, 2002.

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37

Latent Variable and Latent Structure Models. Routledge, 2013.

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38

Brown, Timothy A. Latent Variable Measurement Models. Oxford University Press, 2013. http://dx.doi.org/10.1093/oxfordhb/9780199934898.013.0013.

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39

(Editor), George A. Marcoulides, and Irini Moustaki (Editor), eds. Latent Variable and Latent Structure Models (Quantitative Methodology Series). Lawrence Erlbaum, 2002.

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40

1944-, Haagen Klaus, Bartholomew David J, and Deistler M, eds. Statistical modelling and latent variables. North-Holland, 1993.

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41

R, Hancock Gregory, and Samuelsen Karen M, eds. Advances in latent variable mixture models. Information Age Pub., 2008.

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42

Everett, B. An Introduction to Latent Variable Models. Springer, 2011.

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43

Carpita, Maurizio, Eugenio Brentari, and El Mostafa Qannari. Advances in Latent Variables: Methods, Models and Applications. Springer, 2016.

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44

Carpita, Maurizio, Eugenio Brentari, and El Mostafa Qannari. Advances in Latent Variables: Methods, Models and Applications. Springer, 2015.

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45

Lee, Sik-Yum. Handbook of Latent Variable and Related Models. North Holland, 2007.

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46

(Editor), Gregory R. Hancock, and Karen M. Samuelsen (Editor), eds. Advances in Latent Variable Mixture Models (PB). Information Age Publishing, 2007.

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47

Handbook of latent variable and related models. Elsevier/North-Holland, 2006.

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48

(Editor), Gregory R. Hancock, and Karen M. Samuelsen (Editor), eds. Advances in Latent Variable Mixture Models (HC). Information Age Publishing, 2007.

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49

Handbook of Latent Variable and Related Models. Elsevier, 2007. http://dx.doi.org/10.1016/b978-0-444-52044-9.x5000-9.

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50

Sik-Yum, Lee, ed. Handbook of latent variable and related models. North-Holland, 2007.

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