Ebook: Latent Variable Modeling and Applications to Causality

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.

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This volume gathers refereed papers presented at the 1994 UCLA conference on "Latent Variable Modeling and Application to Causality." The papers in this volume are representative of a wide variety of disciplines in which the use of latent varible models is rapidly growing. The volume is divided into two broad sections. The first section covers Path Modela and Causal Reasoning, and the chapters are innovations from contributions in disciplines not traditionally associated with the behavorial sciences, such as computer science and public health. The second section encompasses new approaches to questions of model selection with an emphasis on factor analysis and time varying systems. All the chapters present new results not published elsewhere.

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This volume gathers refereed papers presented at the 1994 UCLA conference on "Latent Variable Modeling and Application to Causality." The papers in this volume are representative of a wide variety of disciplines in which the use of latent varible models is rapidly growing. The volume is divided into two broad sections. The first section covers Path Modela and Causal Reasoning, and the chapters are innovations from contributions in disciplines not traditionally associated with the behavorial sciences, such as computer science and public health. The second section encompasses new approaches to questions of model selection with an emphasis on factor analysis and time varying systems. All the chapters present new results not published elsewhere.
Content:
Front Matter....Pages i-vii
Embedding common factors in a path model....Pages 1-10
Measurement, Causation and Local Independence in Latent Variable Models....Pages 11-28
On the Identification of Nonparametric Structural Models....Pages 29-68
Causal Inference from Complex Longitudinal Data....Pages 69-117
Models as Instruments, With Applications to Moment Structure Analysis....Pages 119-131
Bias and mean square error of the maximum likelihood estimators of the parameters of the intraclass correlation model....Pages 133-147
Latent Variable Growth Modeling with Multilevel Data....Pages 149-161
High-dimensional Full-information Item Factor Analysis....Pages 163-176
Dynamic Factor Models for the Analysis of Ordered Categorical Panel Data....Pages 177-194
Model fitting procedures for nonlinear factor analysis using the errors-in-variables parameterization....Pages 195-210
Multivariate Regression with Errors in Variables: Issues on Asymptotic Robustness....Pages 211-228
Non-Iterative Fitting of the Direct Product Model for Multitrait-Multimethod Matrices....Pages 229-245
An EM Algorithm for ML Factor Analysis with Missing Data....Pages 247-258
Optimal Conditionally Unbiased Equivariant Factor Score Estimators....Pages 259-281
Back Matter....Pages 283-284

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This volume gathers refereed papers presented at the 1994 UCLA conference on "Latent Variable Modeling and Application to Causality." The papers in this volume are representative of a wide variety of disciplines in which the use of latent varible models is rapidly growing. The volume is divided into two broad sections. The first section covers Path Modela and Causal Reasoning, and the chapters are innovations from contributions in disciplines not traditionally associated with the behavorial sciences, such as computer science and public health. The second section encompasses new approaches to questions of model selection with an emphasis on factor analysis and time varying systems. All the chapters present new results not published elsewhere.
Content:
Front Matter....Pages i-vii
Embedding common factors in a path model....Pages 1-10
Measurement, Causation and Local Independence in Latent Variable Models....Pages 11-28
On the Identification of Nonparametric Structural Models....Pages 29-68
Causal Inference from Complex Longitudinal Data....Pages 69-117
Models as Instruments, With Applications to Moment Structure Analysis....Pages 119-131
Bias and mean square error of the maximum likelihood estimators of the parameters of the intraclass correlation model....Pages 133-147
Latent Variable Growth Modeling with Multilevel Data....Pages 149-161
High-dimensional Full-information Item Factor Analysis....Pages 163-176
Dynamic Factor Models for the Analysis of Ordered Categorical Panel Data....Pages 177-194
Model fitting procedures for nonlinear factor analysis using the errors-in-variables parameterization....Pages 195-210
Multivariate Regression with Errors in Variables: Issues on Asymptotic Robustness....Pages 211-228
Non-Iterative Fitting of the Direct Product Model for Multitrait-Multimethod Matrices....Pages 229-245
An EM Algorithm for ML Factor Analysis with Missing Data....Pages 247-258
Optimal Conditionally Unbiased Equivariant Factor Score Estimators....Pages 259-281
Back Matter....Pages 283-284
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