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Origin of logistic regression. Basic notions, concepts.
Logit analysis of Contingency tables-part 1. Basic theory and introduction.
Logit analysis of Contingency tables-part 2. Logit analysis for two, three, four - way tables.
Binary logistic model - part 1. Basic notions and special cases of the logistic model.
Binary logistic model - part 2. Estimation of the logistic model, general principles.
Binary logistic model - part 3. Model with interaction terms, modeling strategy guidelines.
Binary logistic model - part 4. Coding and estimation, detailed outputs, confidence intervals.
Binary logistic model - part 5. Estimation and detailed outputs, assessing interaction, goodness of fit, statistics measuring predictive power, other methods of model evaluation and validation.
Problems with the estimation of logistic models.
Problems arising in the construction of logistic models.
Ordinal Logistic Regression Model
Multinomial Logistic Regression Model.
Loglinear models for contingency tables. Building and extending loglinear models.
Predictive modelling based on logistic regression.
Logistic and loglinear models estimation and evaluation in R & PYTHON.
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