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Applied Logistic Regression: Course Outline

This course provides theoretical and practical training on the increasingly popular logistic regression model, which has become the standard analytical method for use with a binary response variable.

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Course Outline

  • Fitting simple and multiple Logistic Regression Models using MLE.
  • Non-iterative weighted Least Squares and discriminant functional analysis methods.
  • Dichotomous.
  • Polytomous and Continuous Independent Variables.
  • Multivariate Case.
  • Interaction and Confounding.
  • Estimation of odds ratios in the presence of interaction.
  • Model-building Strategies and Methods for Logistics Regression.

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