Latent Variable Modeling and Applications to Causality
. Ed(s): Berkane, M. (University of Cambridge, Massachusetts, USA)
ISBN 10: 0387949178 ISBN 13: 9780387949178
Editore: Springer-Verlag New York Inc., 1997
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Collates papers from a 1994 UCLA conference on "Latent Variable Modeling and Application to Causality". The first part covers path modela and causal reasoning, while the second focuses on approaches to questions of model selection with an emphasis on factor analysis and time varying systems. Editor(s): Berkane, M. (University of Cambridge, Massachusetts, USA). Series: Lecture Notes in Statistics. Num Pages: 292 pages, biography. BIC Classification: JHBC; PBT; PBWH. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 233 x 156 x 17. Weight in Grams: 428. . 1997. Softcover reprint of the original 1st ed. 1997. Paperback. . . . . Books ship from the US and Ireland. Codice articolo V9780387949178
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Collates papers presented at an 1994 UCLA conference on "Latent Varaible Modeling and Application to Causality". The selection of the papers aims to be representative of a wide variety of disciplines in which the use of latent variable models is rapidly growing. The first section covers path models and causal reasoning, and the chapters are innovations from contributions in disciplines not traditionally associated with the behavioural sciences, such as computer and public health. The second section encompasses new approaches to questions of model selection with an emphasis on factor analysis and time varying systems.
Contenuti: Causality and Path Models.- Embedding Common factors in a Path Model.- Measurement, Causation and Local Independence in Latent Variable Models.- On the Identifiability of Nonparametric Structural Models.- Estimating the Causal effects of Time Varying Endogeneous Treatments by G-Estimation of Structural Nested Models.- Latent Variables.- Model as Instruments, with Applications to Moment Structure Analysis.- Bias and Mean Square Error of the Maximum Likelihood Estimators of the Parameters of the Intraclass Correlation Model.- Latent Variable Growth Modeling with Multilevel Data.- High-Dimensional Full-Information Item Factor Analysis.- Dynamic Factor Models for the Analysis of Ordered Categorical Panel data.- Model Fitting Procedures for Nonlinear Factor Analysis Using the Errors-in-Variables Parameterization.- Multivariate Regression with Errors in Variables: Issues on Asymptotic Robustness.- Non-Iterative fitting of the Direct Product Model for Multitrait-Multimethod Correlation Matrices.- An EM Algorithm for ML Factor Analysis with Missing Data.- Optimal Conditionally Unbiased Equivariant Factor Score Estimators.
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Titolo: Latent Variable Modeling and Applications to...
Casa editrice: Springer-Verlag New York Inc.
Data di pubblicazione: 1997
Legatura: Brossura
Condizione: New
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Latent Variable Modeling and Applications to Causality (Lecture Notes in Statistics, 120)
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Latent Variable Modeling and Applications to Causality
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Latent Variable Modeling and Applications to Causality (Lecture Notes in Statistics, 120)
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Latent Variable Modeling and Applications to Causality (Paperback)
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Springer-Verlag New York Inc., New York, NY, 1997
ISBN 10: 0387949178
ISBN 13: 9780387949178
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Paperback. Condizione: new. Paperback. Collates papers presented at an 1994 UCLA conference on "Latent Varaible Modeling and Application to Causality". The selection of the papers aims to be representative of a wide variety of disciplines in which the use of latent variable models is rapidly growing. The first section covers path models and causal reasoning, and the chapters are innovations from contributions in disciplines not traditionally associated with the behavioural sciences, such as computer and public health. The second section encompasses new approaches to questions of model selection with an emphasis on factor analysis and time varying systems. This volume gathers refereed papers presented at the 1994 UCLA conference on "La tent Variable Modeling and Application to Causality. Deleeuw extends exploratory factor analysis models by including time as a variable and allowing for discrete and ordi nal latent variables. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9780387949178
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Latent Variable Modeling and Applications to Causality
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ISBN 10: 0387949178
ISBN 13: 9780387949178
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This volume gathers refereed papers presented at the 1994 UCLA conference on 'La tent Variable Modeling and Application to Causality. ' The meeting was organized by the UCLA Interdivisional Program in Statistics with the purpose of bringing together a group of people who have done recent advanced work in this field. The papers in this volume are representative of a wide variety of disciplines in which the use of latent variable models is rapidly growing. The volume is divided into two broad sections. The first section covers Path Models and Causal Reasoning and the papers are innovations from contributors in disciplines not traditionally associated with behavioural sciences, (e. g. computer science with Judea Pearl and public health with James Robins). Also in this section are contri butions by Rod McDonald and Michael Sobel who have a more traditional approach to causal inference, generating from problems in behavioural sciences. The second section encompasses new approaches to questions of model selection with emphasis on factor analysis and time varying systems. Amemiya uses nonlinear factor analysis which has a higher order of complexity associated with the identifiability condi tions. Muthen studies longitudinal hierarchichal models with latent variables and treats the time vector as a variable rather than a level of hierarchy. Deleeuw extends exploratory factor analysis models by including time as a variable and allowing for discrete and ordi nal latent variables. Arminger looks at autoregressive structures and Bock treats factor analysis models for categorical data.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 296 pp. Englisch. Codice articolo 9780387949178
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Latent Variable Modeling and Applications to Causality
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This volume gathers refereed papers presented at the 1994 UCLA conference on 'La tent Variable Modeling and Application to Causality. ' The meeting was organized by the UCLA Interdivisional Program in Statistics with the purpose of bringing together a group of people who have done recent advanced work in this field. The papers in this volume are representative of a wide variety of disciplines in which the use of latent variable models is rapidly growing. The volume is divided into two broad sections. The first section covers Path Models and Causal Reasoning and the papers are innovations from contributors in disciplines not traditionally associated with behavioural sciences, (e. g. computer science with Judea Pearl and public health with James Robins). Also in this section are contri butions by Rod McDonald and Michael Sobel who have a more traditional approach to causal inference, generating from problems in behavioural sciences. The second section encompasses new approaches to questions of model selection with emphasis on factor analysis and time varying systems. Amemiya uses nonlinear factor analysis which has a higher order of complexity associated with the identifiability condi tions. Muthen studies longitudinal hierarchichal models with latent variables and treats the time vector as a variable rather than a level of hierarchy. Deleeuw extends exploratory factor analysis models by including time as a variable and allowing for discrete and ordi nal latent variables. Arminger looks at autoregressive structures and Bock treats factor analysis models for categorical data. 296 pp. Englisch. Codice articolo 9780387949178
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Latent Variable Modeling and Applications to Causality
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ISBN 10: 0387949178
ISBN 13: 9780387949178
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This volume gathers refereed papers presented at the 1994 UCLA conference on 'La tent Variable Modeling and Application to Causality. ' The meeting was organized by the UCLA Interdivisional Program in Statistics with the purpose of bringing together a group of people who have done recent advanced work in this field. The papers in this volume are representative of a wide variety of disciplines in which the use of latent variable models is rapidly growing. The volume is divided into two broad sections. The first section covers Path Models and Causal Reasoning and the papers are innovations from contributors in disciplines not traditionally associated with behavioural sciences, (e. g. computer science with Judea Pearl and public health with James Robins). Also in this section are contri butions by Rod McDonald and Michael Sobel who have a more traditional approach to causal inference, generating from problems in behavioural sciences. The second section encompasses new approaches to questions of model selection with emphasis on factor analysis and time varying systems. Amemiya uses nonlinear factor analysis which has a higher order of complexity associated with the identifiability condi tions. Muthen studies longitudinal hierarchichal models with latent variables and treats the time vector as a variable rather than a level of hierarchy. Deleeuw extends exploratory factor analysis models by including time as a variable and allowing for discrete and ordi nal latent variables. Arminger looks at autoregressive structures and Bock treats factor analysis models for categorical data. Codice articolo 9780387949178
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Latent Variable Modeling and Applications to Causality (Lecture Notes in Statistics, 120)
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