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1. Foundations of Categorical Data
2. Descriptive Analysis of Categorical Data
3. Probability Foundations for Categorical Data
4. Single Variable Inference
5. Two-Variable Analysis
6. Stratified Analysis
7. Logistic Regression
8. Multinomial Response Models
9. Loglinear Models
10. Advanced Topics
11. Computational Methods
  1. Statistics

Categorical Data Analysis

1. Foundations of Categorical Data
2. Descriptive Analysis of Categorical Data
3. Probability Foundations for Categorical Data
4. Single Variable Inference
5. Two-Variable Analysis
6. Stratified Analysis
7. Logistic Regression
8. Multinomial Response Models
9. Loglinear Models
10. Advanced Topics
11. Computational Methods
11.
Computational Methods
11.1.
Software Implementation
11.1.1.
R Packages and Functions
11.1.2.
SAS Procedures
11.1.3.
SPSS Methods
11.1.4.
Python Libraries
11.2.
Large Sample Approximations
11.2.1.
Asymptotic Theory
11.2.2.
Continuity Corrections
11.2.3.
Finite Sample Adjustments
11.3.
Exact Methods
11.3.1.
Enumeration Algorithms
11.3.2.
Network Algorithms
11.3.3.
Monte Carlo Methods
11.4.
Bootstrap Methods
11.4.1.
Nonparametric Bootstrap
11.4.2.
Parametric Bootstrap
11.4.3.
Confidence Interval Construction

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10. Advanced Topics

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1. Foundations of Categorical Data

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