Estimating Latent Structure Models with Categorical Variables: One-Step Versus Three-Step Estimators
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Tài liệu tham khảo
Steiger, 1978, Theory Construction and Data Analysis in Behavioral Sciences, 136
Lazarsfeld, 1950a, Measurement and Prediction, 413
Vermunt, 1997a, Loglinear Models for Event History Analysis
Croon, 2002, Latent Variable and Latent Structure Models, 195
Heinen, 1996, Latent Class and Discrete Latent Trait Models: Similarities and Differences
Bolck, 1997, On the Use of Latent Scores in Causal Models for Categorical Variables
Bartholomew, 1999, Latent Variable Models and Factor Analysis
Haberman, 1979, Analysis of Qualitative Data: New Developments, 2
Hagenaars, 1990, Categorical Longitudinal Data: Log-Linear Panel, Trend and Cohort Analysis
Lazarsfeld, 1950b, Measurement and Prediction, 362
Vermunt, 2000, Latent Gold; User's Guide
These models are also denoted as DLM (Directed Loglinear Models) with latent variables.
Lazarsfeld, 1968, Latent Structure Analysis
Bentler, 1996, Latent Variable Modeling and Applications to Causality, 259
Van de Pol, 1996, PANMARK 3 User's Manual
Whittaker, 1990, Graphical Models in Applied Multivariate Statistics
Occasionally a third approach is proposed in which, first, an appropriate “stand-alone” measurement model is defined and its parameters are estimated. In the next step, the parameters of the causal model are estimated with the parameters of the measurement model fixed to their values obtained in the first step. This two-step approach will not be discussed further in this paper.
Croon, 1997, On the Use of Factor Scores in Structural Equations Models
Vermunt, 1997b, ℓEM: A General Program for the Analysis of Categorical Data
Hagenaars Jacques A. , McCutcheon Allan L. 2002. Applied Latent Class Analysis. Cambridge: Cambridge University Press.