EPI 5345 Applied Logistic Regression

1.5 units
Epidemiology and Public Health
Faculty of Medicine
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.

Components:

Lecture

Requirements:

EPI 5345 is a corequisite to EPI 5340 .

Previously Offered Terms:

Winter
All Professors
A Average (9.023)
Most Common: A+ (53%)
131 students

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NS

F

D

C

B

A-

A+

Marie-Hélène Roy-Gagnon

3 sections from Winter 2018 to Winter 2024

A Average (9.177)
Most Common: A+ (61%)
62 students

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S

NS

F

D

C

B

A-

A+

Chris Gravel

Winter 2023 - A00

A Average (8.647)
Most Common: A- (35%)
34 students

P

S

NS

F

D

C

B

A-

A+

Unknown Professor

Winter 2022 - AV00

A Average (9.114)
Most Common: A+ (57%)
35 students

P

S

NS

F

D

C

B

A-

A+