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Introduction to the Statistical Analysis of Categorical Data [electronic resource] / by Erling B. Andersen.

By: Material type: Computer fileComputer filePublication details: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1997.Edition: 1st ed. 1997Description: X, 265 p. online resourceISBN:
  • 9783642591235
Subject(s): DDC classification:
  • 519.2 23
Online resources:
Contents:
1 Introduction -- 1.1 The two-way table -- 2 Basic Theory -- 2.1 Introduction -- 2.2 Exponential families -- 2.3 Statistical inference in an exponential family -- 2.4 The binomial distribution -- 2.5 The multinomial distribution -- 2.6 The Poisson distribution -- 2.7 Composite hypotheses -- 2.8 Applications to the multinomial distribution -- 2.9 Log-linear models -- 2.10 The two-way contingency table -- 2.11 The numerical solution of the likelihood equations for the log-linear model -- 2.12 Bibliographical notes -- 2.13 Exercises -- 3 Three-way contingency tables -- 3.1 Log-linear models -- 3.2 Log-linear hypotheses -- 3.3 Estimation -- 3.4 Testing hypotheses -- 3.5 Interpretation of the log-linear parameters -- 3.6 Choice of model -- 3.7 Detection of model deviations -- 3.8 Bibliographical notes -- 3.9 Exercises -- 4 Multi-dimensional contingency tables -- 4.1 The log-linear model -- 4.2 Classification and interpretation of log-linear models -- 4.3 Choice of model -- 4.4 Diagnostics -- 4.5 Model search strategies -- 4.6 Bibliographical notes -- 4.7 Exercises -- 5 Incomplete Tables -- 5.1 Random and structural zeros -- 5.2 Counting the number of degrees of freedom -- 5.3 Validity of the X2-approximation -- 5.4 Exercises -- 6 The Logit Model -- 6.1 The logit model -- 6.2 Hypothesis testing in the logit model -- 6.3 Logit models with higher order interactions -- 6.4 The logit model as a regression model -- 6.5 Bibliographical notes -- 6.6 Exercises -- 7 Logistic Regression Analysis -- 7.1 The logistic regression model -- 7.2 Estimation in the logistic regression model -- 7.3 Numerical solution of the likelihood equations -- 7.4 Checking the fit of the model -- 7.5 Hypothesis testing -- 7.6 Diagnostics -- 7.7 Predictions -- 7.8 Dummy variables -- 7.9 Polytomous response variables -- 7.10 Bibliographical notes -- 7.11 Exercises -- 8 Association Models -- 8.1 Introduction -- 8.2 Symmetry models -- 8.3 Marginal homogeneity -- 8.4 RC-association models -- 8.5 Correspondence analysis -- 8.6 Bibliographical notes -- 8.5 Exercises -- Appendix Solutions and output to selected exercises -- References.
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1 Introduction -- 1.1 The two-way table -- 2 Basic Theory -- 2.1 Introduction -- 2.2 Exponential families -- 2.3 Statistical inference in an exponential family -- 2.4 The binomial distribution -- 2.5 The multinomial distribution -- 2.6 The Poisson distribution -- 2.7 Composite hypotheses -- 2.8 Applications to the multinomial distribution -- 2.9 Log-linear models -- 2.10 The two-way contingency table -- 2.11 The numerical solution of the likelihood equations for the log-linear model -- 2.12 Bibliographical notes -- 2.13 Exercises -- 3 Three-way contingency tables -- 3.1 Log-linear models -- 3.2 Log-linear hypotheses -- 3.3 Estimation -- 3.4 Testing hypotheses -- 3.5 Interpretation of the log-linear parameters -- 3.6 Choice of model -- 3.7 Detection of model deviations -- 3.8 Bibliographical notes -- 3.9 Exercises -- 4 Multi-dimensional contingency tables -- 4.1 The log-linear model -- 4.2 Classification and interpretation of log-linear models -- 4.3 Choice of model -- 4.4 Diagnostics -- 4.5 Model search strategies -- 4.6 Bibliographical notes -- 4.7 Exercises -- 5 Incomplete Tables -- 5.1 Random and structural zeros -- 5.2 Counting the number of degrees of freedom -- 5.3 Validity of the X2-approximation -- 5.4 Exercises -- 6 The Logit Model -- 6.1 The logit model -- 6.2 Hypothesis testing in the logit model -- 6.3 Logit models with higher order interactions -- 6.4 The logit model as a regression model -- 6.5 Bibliographical notes -- 6.6 Exercises -- 7 Logistic Regression Analysis -- 7.1 The logistic regression model -- 7.2 Estimation in the logistic regression model -- 7.3 Numerical solution of the likelihood equations -- 7.4 Checking the fit of the model -- 7.5 Hypothesis testing -- 7.6 Diagnostics -- 7.7 Predictions -- 7.8 Dummy variables -- 7.9 Polytomous response variables -- 7.10 Bibliographical notes -- 7.11 Exercises -- 8 Association Models -- 8.1 Introduction -- 8.2 Symmetry models -- 8.3 Marginal homogeneity -- 8.4 RC-association models -- 8.5 Correspondence analysis -- 8.6 Bibliographical notes -- 8.5 Exercises -- Appendix Solutions and output to selected exercises -- References.

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