Sykdomspulsen has published a short course that teaches students to run “normal regressions” in situations where the data structure would ordinarily prohibit you from running regression models. These situations mostly pertain to clusters of correlated data.

You can find the course “Longitudinal Analysis for Surveillance” in the Learning page.

When dealing with longitudinal data, there are two kinds of analyses that can be performed:

- “Time series” analyses generally deal with one variable. The aim is
to then predict the future only using the previous observations. A
common example would be to predict tomorrow’s temperature, using today’s
and yesterday’s temperature as exposures.
**We will not be focusing on these kinds of analyses in this course.** - “Regression analyses” are very similar to ordinary regressions that
you have been working with for many years. The only difference is that
they have more advanced data structures that your current methods cannot
handle. For example, if you want to see how the number of tuberculosis
patients (outcome) is affected by the number of immigrants to Norway
(exposure) over a 20 year period, then the number of patients in each
year might be associated with each other, which might break assumptions
of the regression models that you normally use (independent residuals).
To account for the advanced structure of the data (correlation between
different years) we will use more advanced regression techniques.
**This will be the focus of the course.**

If you see mistakes or want to suggest changes, please create an issue on the source repository.

Text and figures are licensed under Creative Commons Attribution CC BY 4.0. Source code is available at https://github.com/sykdomspulsen-org/sykdomspulsen-org.github.io, unless otherwise noted. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".

For attribution, please cite this work as

White (2022, Jan. 24). Sykdomspulsen: New Course: Longitudinal Analysis for Surveillance. Retrieved from https://docs.sykdomspulsen.no/posts/2022-01-24-new-course-longitudinal-analysis-for-surveillance/

BibTeX citation

@misc{white2022new, author = {White, Richard Aubrey}, title = {Sykdomspulsen: New Course: Longitudinal Analysis for Surveillance}, url = {https://docs.sykdomspulsen.no/posts/2022-01-24-new-course-longitudinal-analysis-for-surveillance/}, year = {2022} }