Latent Variables Analysis
Applications for Developmental Research
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Latent Variables Analysis by Alexander Von Eye
Book DescriptionIn this volume, leading researchers examine how latent variables can be incorporated in a variety of data-analysis strategies, such as structural equation modelling, regression analysis, log-linear modelling and prediction analysis. The contributors also discuss how latent variables analysis can be applied in developmental psychology research using methods such as cohort-time of measurement-age analysis, log-linear modelling of behaviour genetics hypothesis and analyses of repeatedly observed state measures. Detailed explanations of computations and software packages are included with each statistical method.
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Book DetailsISBN: 9780803953314
(216mm x 140mm x 28mm)
Imprint: SAGE Publications Inc
Publisher: SAGE Publications Inc
Publish Date: 20-Oct-1994
Country of Publication: United States
Books By Author Alexander Von Eye
Statistics and Causality, Hardback (July 2016)
A one-of-a-kind guide to identifying and dealing with modern statistical developments in causality Written by a group of well-known experts, Statistics and Causality: Methods for Applied Empirical Research focuses on the most up-to-date developments in statistical methods in respect to causality.
Log-Linear Modeling, Hardback (January 2013)
Utilizing real-world examples along with R and SYSTAT software, this book describes the multidisciplinary applications of new and advanced methods, models, and applications of log-linear modeling.
Advances in Configural Frequency Analysis, Hardback (June 2010)
Using real-world data examples, this book shows how to use the configural frequency analysis (CFA) techniques to analyze categorical data.
Structural Equation Modeling, Paperback (March 2009)» View all books by Alexander Von Eye
Structural equation modelling (SEM) is a technique that is used to estimate, analyse and test models that specify relationships among variables.
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Author Biography - Alexander Von Eye
Methodology and Statistics, Michigan State University.
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