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Master CDA and GLM applications
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Module 1
Foundations of Categorical Data Analysis
1
Data Types and Summary Measures
Distinguish between categorical, ordinal, and nominal data and identify appropriate summary measures for each.
2
Contingency Tables from Raw Data
Construct and interpret a contingency table from raw categorical data.
3
Understanding Sampling Schemes and Their Analytical Implications
Explain different sampling schemes (e.g., product-multinomial, multinomial) and their implications for analysis.
4
Contingency Table Distributions: Joint, Marginal, and Conditional
Compute and interpret joint, marginal, and conditional distributions from a contingency table.
5
Difference in Proportions for 2x2 Tables
Define, compute, and interpret the difference in proportions for a 2×2 table.
6
Calculating and Interpreting Relative Risk
Define, compute, and interpret the relative risk for a 2×2 table.
7
Odds Ratios in 2x2 Tables
Define, compute, and interpret the odds ratio for a 2×2 table, including its key properties.
8
Odds Ratio vs. Relative Risk: Choosing the Right Measure
Explain when the odds ratio vs. relative risk is the appropriate measure of association based on the study design.
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Testing for Independence in Contingency Tables