Statistical Modelling and Latent Variables
Proceedings of the International Workshop, Trento, Italy, 15-17 July 1991
Published on 10. June 1993
Book
Hardback
366 pages
978-0-444-89832-6 (ISBN)
Description
Statistical methods based on models with latent variables play an important role in the analysis of multivariate data. The subject can be approached theoretically or in an empirical, pragmatic way. The statistical problem is to make inferences about the latent variables and the relationships between them. Errors-in-variables models, factor analysis and latent structure models are all examples of this approach. This volume presents a selection of invited and contributed papers which address the problems involved in developing a unifying statistical theory for latent variable models.
Statistical methods based on models with latent variables play an important role in the analysis of multivariate data. The subject can be approached theoretically or in an empirical, pragmatic way. The statistical problem is to make inferences about the latent variables and the relationships between them. Errors-in-variables models, factor analysis and latent structure models are all examples of this approach. This volume presents a selection of invited and contributed papers which address the problems involved in developing a unifying statistical theory for latent variable models.
Statistical methods based on models with latent variables play an important role in the analysis of multivariate data. The subject can be approached theoretically or in an empirical, pragmatic way. The statistical problem is to make inferences about the latent variables and the relationships between them. Errors-in-variables models, factor analysis and latent structure models are all examples of this approach. This volume presents a selection of invited and contributed papers which address the problems involved in developing a unifying statistical theory for latent variable models.
More details
Language
English
Place of publication
Oxford
United Kingdom
Publishing group
Elsevier Science & Technology
Target group
College/higher education
Professional and scholarly
Dimensions
Height: 230 mm
ISBN-13
978-0-444-89832-6 (9780444898326)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Persons
Content
Criminometrics, Latent Variables, and Panel Data (J. Aasness, E. Eide, T. Skjerpen). Scale Construction by Maximizing Reliability (D.J. Bartholomew, M. Knott). Finite Sample Properties of Limited Information Estimation: An Algebraic Approach (P.A. Bekker). Structural Equation Models as Nonlinear Regression Models (P.M. Bentler). Stochastic Frontier and Switching Regression Models with Latent Variables (R. Colombi). Latent Class Models with Ordered Latent Classes: An Approach to Nonparametric Latent Trait Modelling (M.A. Croon). System Identification and Errors in the Variables (M. Deistler, W. Scherrer). Principal Components and Proportionality in Patterned Covariance Matrices (B.D. Flury, B. Neuenschwander). Errors-in-Variables Identification and Model Uniqueness (R.P. Guidorzi). Measurement Error Models with Unequal Error Variances (N.A. Hasabelnaby, W.A. Fuller). Latent Variable Modelling with Ordinal Variables (K.G. Joereskog). Asymptotic Properties of Statistical Inference Based on Fisher Consistent Estimators in the Analysis of Covariance Structures (Y. Kano). Imposed Quasi-Normality in Covariance Structure Analysis (R. Koning, H. Neudecker, T. Wansbeek). Structural Equation Models with Hierarchical Data (S.-Y. Lee, W.-Y. Poon). Global Optimization Criteria of the PLS-Algorithm in Recursive Path Models with Latent Variables (H. Mathes). Structural Equation Models with Transformed Variables (A. Mooijaart). Individual Unit Models versus Structural Equations: Growth Curve Examples (D. Rogosa). Multi-Sample Analysis of Moment-Structures: Asymptotic Validity of Inferences Based on Second-Order Moments (A. Satorra). Consistency at Large in Models with Latent Variables (H. Schneeweiss). A DYMIMIC Model of Employment: Another Look at Some Issues of Formulation, Identification and Estimation (U. Trivellato, S. Bordignon, C. Gaetan). General Least Squares Regression in Linear Errors-in-Variables Models with Correlated Errors (L. Wang).