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The Statistical Analysis of Categorical Data

Author: Erling B Andersen
Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 1990.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:
This book is about the analysis of categorical data with special emphasis on applications in economics, political science and the social sciences. The book gives a brief theoretical introduction to log-linear modeling of categorical data, then gives an up-to-date account of models and methods for the statistical analysis of categorical data, including recent developments in logistic regression models, correspondence  Read more...
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Genre/Form: Electronic books
Statistics
Additional Physical Format: Print version:
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Erling B Andersen
ISBN: 9783642972256 364297225X
OCLC Number: 851381412
Description: 1 online resource (ix, 523 pages 41 illustrations)
Contents: 1. Categorical Data --
2. Preliminaries --
2.1 Statistical models --
2.2 Estimation --
2.3 Testing statistical hypotheses --
2.4 Checking the model --
3. Statistical Inference --
3.1 Log-linear models --
3.2 The one-dimensional case --
3.3 The multi-dimensional case --
3.4 Testing composite hypotheses --
3.5 The parametric multinomial distribution --
3.6 Generalized linear models --
3.7 Solution of likelihood equations --
3.8 Exercises --
4. Two-way Contingency Tables --
4.1 Three models --
4.2 The 2x2 table --
4.3 The log-linear parameterization --
4.4 The hypothesis of no interaction --
4.5 Residual analysis --
4.6 Exercises --
5. Three-way Contingency Tables --
5.1 The log-linear parameterization --
5.2 Hypotheses in a three-way table --
5.3 Hypothesis testing --
5.4 Decomposition of the test statistic --
5.5 Detection of model departures --
5.6 Exercises --
6. Multi-dimensional Contingency Tables --
6.1 The log-linear model --
6.2 Interpretation of log-linear models --
6.3 Search for a model --
6.4 Diagnostics for model departures --
6.5 Exercises --
7. Incomplete Tables, Separability and Collapsibility --
7.1 Incomplete tables --
7.2 Two-way tables and quasi-independence --
7.3 Higher order tables. Separability --
7.4 Colapsibility --
7.5 Exercises --
8. The Logit Model --
8.1 The logit model with binary explanatory variables --
8.2 The logit model with polytomous explanatory variables --
Exercises --
9. Logistic Regression Analysis --
9.1 The logistic regression model --
9.2 Regression diagnostics --
9.3 Predictions --
9.4 Polytomous response variables --
9.5 Exercises --
10 Models for the Interactions --
10.1 Introduction --
10.2 Symmetry models --
10.3 Marginal homogeneity --
10.4 Models for mobility tables --
10.5 Association models --
10.6 RC-association models --
10.7 Log-linear association models --
10.8 Exercises --
11. Correspondance Analysis --
11.1 Correspondance analysis for two-way tables --
11.2 Correspondance analysis for multiway tables --
11.3 Comparison of models --
11.4 Exercises --
12. Latent Structure Analysis --
12.1 Latent structure models --
12.2 Latent class models --
12.3 Continuous latent structure models --
12.4 The EM-algorithm --
12.5 Estimation in the latent class model --
12.6 Estimation in the continuous latent structure model --
12.7 Testing the goodness of fit --
12.8 Diagnostics --
12.9 Score models with varying discriminating powers --
12.10 Comparison of latent structure models --
12.11 Estimation of the latent variable --
12.12 Exercises --
References --
Author Index --
Examples with Data.
Responsibility: by Erling B. Andersen.

Abstract:

This book is about the analysis of categorical data with special emphasis on applications in economics, political science and the social sciences. The book gives a brief theoretical introduction to log-linear modeling of categorical data, then gives an up-to-date account of models and methods for the statistical analysis of categorical data, including recent developments in logistic regression models, correspondence analysis and latent structure analysis. Also treated are the RC association models brought to prominence in recent years by Leo Goodman. New statistical features like the use of association graphs, residuals and regression diagnostics are carefully explained, and the theory and methods are extensively illustrated by real-life data. The book introduces readers to the latest developments in categorical data analysis, and are shown how real life data can be analysed, how conclusions are drawn and how models are modified.

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