Latent variable modeling and applications to causality /
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 di...
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| Format: | eBook |
| Language: | English |
| Published: |
New York :
Springer,
[1997]
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| Series: | Lecture notes in statistics (Springer-Verlag) ;
v. 120. |
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
Table of Contents:
- 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
- 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 parametrization
- 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.