Carleton University · EPIJ 5345

Applied Logistic Regression

Credits : 0.25 creditReference year : 2026-27

Description

Foundation of model estimation: maximum likelihood; modeling dichotomous outcome (dependent) variables: logistic regression; logistic models with several independent variables; interpretation of model parameters; model-building strategies; assessing the fit of the model; regression diagnostics. Classes will include hands-on modeling examples using SAS statistical software.

Prerequisites

  • Prerequisite(s): EPI 5340.

Conditions and arrangements

  • Prerequisite(s): EPI 5340.
Reference text in its original language

Foundation of model estimation: maximum likelihood; modeling dichotomous outcome (dependent) variables: logistic regression; logistic models with several independent variables; interpretation of model parameters; model-building strategies; assessing the fit of the model; regression diagnostics. Classes will include hands-on modeling examples using SAS statistical software.

  • Prerequisite(s): EPI 5340.

Sources and references

Dates and sources are retained to help you verify the information. Translations are provided to facilitate reading; the official source governs conditions and requirements.

Source reference : https://calendar.carleton.ca/grad/courses/EPIJ/

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