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Wednesday and Thursday 21–22 February 2024 (Online)

This 2-day online course provides an extensive introduction to regression modelling approaches. The scope of the course runs from basic principles of regression methods, deciphering the output of statistical analyses, and the practicalities of running these various regression methods.

As part of this course you will be encouraged to think about broader study design issues, including how to deal with confounding, interactions and variable selection. The practical components can be run using SAS, Stata, or R software.

Register now

Public Health Summer School Banner 2024

Topics covered

  • Linear regression
  • Logistic regression
  • Poisson regression
  • Adjusting for confounders and allowing for interactions
  • Principled selection of model variables

Style of course

Taught via Zoom with computer practicals – hands-on course combining taught overview, hints on programming practices, and practical exercises.

Participants need to have a computer for this course with R, SAS or Stata software installed, alongside Zoom.

Who should attend?

This is an intermediate-level statistics course intended for researchers/research students who need to use regression modelling in their work. Participants should have a reasonable understanding of basic statistical methods (e.g. hypothesis testing, confidence intervals) and have reasonable proficiency with their chosen software package (able to import data sets, generate new variables, run basic statistical methods like descriptive statistics and simple hypothesis tests).

Draft timetable

TimeSessionPresenter(s)
Day 1  
9:00am Welcome and introductions James Stanley
9:15am Foundations and linear regression James Stanley
10:30am Morning tea 
11:00am Linear regression practical James Stanley
12:30pm Lunch break 
1:15pm Logistic regression James Stanley
3:00pm Afternoon tea 
3:30pm Logistic regression practical James Stanley
4:45pm Finish  
Day 2  
9:00am Recap and queries from yesterday James Stanley
9:15am Model selection and Poisson regression James Stanley
10:30am Morning break 
10:45am Poisson regression practical James Stanley
12:15pm Lunch break 
1:00pm General extensions of regression models: Continuous predictors and interactions James Stanley
2:15pm Afternoon break 
2:30pm General extensions practical James Stanley
3:30pm Conclusion and evaluation James Stanley
3:45pm Finish  

Teaching staff

Dr James Stanley is a Research Associate Professor and consulting biostatistician at the University of Otago, Wellington. He has 15 years experience in using and teaching regression models for applied health research.

Location

This two-day course will be held online via zoom.

Course cost and registration

$450 early bird, $600 after Wednesday 20 December 2023.

A 50% discount is available to full-time students, those unwaged and University of Otago staff.

Register now

For more information please contact the course convenor

Contact name
James Stanley
Email
james.stanley@otago.ac.nz
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