Latent Variable Modeling and Applications to Causality

Chapter 1 Embedding common factors in a path model

Chapter 2 Measurement, Causation and Local Independence in Latent Variable Models

Chapter 3 On the Identification of Nonparametric Structural Models

Chapter 4 Causal Inference from Complex Longitudinal Data

Chapter 5 Models as Instruments, With Applications to Moment Structure Analysis

Chapter 6 Bias and mean square error of the maximum likelihood estimators of the parameters of the intraclass correlation model

Chapter 7 Latent Variable Growth Modeling with Multilevel Data

Chapter 8 High-dimensional Full-information Item Factor Analysis

Chapter 9 Dynamic Factor Models for the Analysis of Ordered Categorical Panel Data

Chapter 10 Model fitting procedures for nonlinear factor analysis using the errors-in-variables parameterization

Chapter 11 Multivariate Regression with Errors in Variables: Issues on Asymptotic Robustness

Chapter 13 An EM Algorithm for ML Factor Analysis with Missing Data

Chapter 14 Optimal Conditionally Unbiased Equivariant Factor Score Estimators