Journal ArticleDOI
Linear Logistic Latent Class Analysis
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In this article, the linear logistic extension of latent class analysis is described and the basic equations of the model state the decomposition of the log-odds of the item latent probabilities and of the class sizes into weighted sums of basic parameters representing the effects of the predictor variables.Abstract:
In the present paper the linear logistic extension of latent class analysis is described. Thereby it is assumed that the item latent probabilities as well as the class sizes can be attributed to some explanatory variables. The basic equations of the model state the decomposition of the log-odds of the item latent probabilities and of the class sizes into weighted sums of basic parameters representing the effects of the predictor variables. Further, the maximum likelihood equations for these effect parameters and statistical tests for goodness-of-fit are given. Finally, an example illustrates the practical application of the model and the interpretation of the model parameters.read more
Citations
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Journal ArticleDOI
Concomitant-Variable Latent-Class Models
TL;DR: In this article, the probability of latent class membership is functionally related to concomitant variables with known distribution, and a general procedure for imposing linear constraints on the parameter estimates is introduced.
Journal ArticleDOI
Latent Variable Regression for Multiple Discrete Outcomes
TL;DR: The concomitant latent class model for analyzing multivariate categorical outcome data is studied, and practical theory for reducing and identifying such models is developed.
Journal ArticleDOI
Latent Structure Analysis of a Set of Multidimensional Contingency Tables
Clifford C. Clogg,Leo A. Goodman +1 more
TL;DR: In this paper, three basic classes of models are considered: (a) models that assume complete homogeneity across tables, (b) model that allow partial homogeneity, and (c) model with complete heterogeneity.
Book
Log-Linear Models for Event Histories
TL;DR: In this article, a log-linear model with Latent Variables and missing data is proposed for event history analysis with missing data and the information matrix in Modified Path Models with Missing Data.
Journal ArticleDOI
Iterative Automated Record Linkage Using Mixture Models
TL;DR: A method is proposed and illustrated that uses marginal information in the database to select mixture models, identifies sets of records for clerks to review based on the models and marginal information, incorporates clerically reviewed data into estimates of model parameters, and classifies pairs as links, nonlinks, or in need of further clerical review.
References
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Book
Linear statistical inference and its applications
TL;DR: Algebra of Vectors and Matrices, Probability Theory, Tools and Techniques, and Continuous Probability Models.
Journal ArticleDOI
Linear Statistical Inference and its Applications
P. G. Moore,C. Radhakrishna Rao +1 more
TL;DR: The theory of least squares and analysis of variance has been studied in the literature for a long time, see as mentioned in this paper for a review of some of the most relevant works. But the main focus of this paper is on the analysis of variance.
Journal ArticleDOI
Latent Structure Analysis.
Journal ArticleDOI
Exploratory latent structure analysis using both identifiable and unidentifiable models
TL;DR: In this article, the authors considered a wide class of latent structure models, which can serve as possible explanations of the observed relationships among a set of m manifest polytomous variables.
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