Course Overview

Students will be able to:

-
Characterize the design of digital cohorts, describe common issues in
the irimplementation and how to increase recruitment and participation
of cohort members

-
Interpret and discuss the results of standard survival analysis, as
well as random forests in survival analysis

-
Demonstrate some familiarities with the concepts of cause and counter
factual

-
Conduct critical appraisals of published epidemiological studies based
on digital cohorts

Learning Achievement

Competence

Course prerequisites

-
Fundamentals of epidemiology (study designs, bias)

-
Fundamentals of biostatistics (hypothesis testing, regression methods)

Grading Philosophy

Assessment during Week 50:

-
Group presentation during tutorials (30%)

-
Written exam (70%)

Course schedule

-
Principle of digital cohorts (9 hours, face-to-face)

-
Communication strategies for digital cohorts (3 hours, e-learning)

-
Causal concepts (9 hours, face-to-face)

-
Standard survival analysis and random forests (12 hours, face-to-face)

Course type

- Lectures - Tutorials - Personal and group-based work

Online Course Requirement

Instructor

Other information

Teaching Unit from M2 Public Health Data Science

Duration: 2 weeks (Weeks 43 and 50)

Language of instruction: English
Mode of delivery: Face-to-face teaching (30 hours) and e-learning (3 hours): lectures, tutorials

Site for Inquiry