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After Work Statistics

How was that again with case number planning? How to interpret an odds ratio? Which test for which data? Although every researching physician should have received a certain statistical education, the important statistical methods and topics are often no longer present once you want to apply them. What now?

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After Work Statistics

As a supplement to our individual statistical consultation service, this lecture series offers a refresher on frequently occuring statistical problems. Right after work! The lectures are explicitly aimed at medical researchers. There are eight different topics, each of which is held twice during a semester. A lecture of 30 minutes plus discussion and you are statistically "up to data" again!

The eight topics are taught in English from October 17 to December 5, 2022 and in German from December 12, 2022 to February 13, 2023 (deutsche Seite) .

 

Time and Location:

mondays from 4pm to 5pm via MS Teams. The link to the lecture (Englisch and German) will be published on the day of the individual event in section Topics and Material on this page.

 

Registry and ECTS:

You may

  • just show up for an individual lecture or
  • gain 0.8 ECTS for attending all eight lectures.
    • If you need to have your participation certified, please register by online form at least two working days prior to the first lecture
    • The online form will be activated on September 26, 2022.
    • you may attend an individual lecture either in German or in English
    • Certificates of attendance will be issued after the last event.

Topics and Material

For dates, presentations, as well as Shiny Apps and videos in German, click here.

Date

Topic

Slides

 

October 17, 2022

So many tests! The agony of choice.

View Slides

 

October 24, 2022

So many questions! Multiple testing.

View Slides

 

October 31, 2022

So many patients? Sample size calculation.

View Slides

 

November 7, 2022

What is it this odds ratio? Logistic regression.

View Slides

 

November 14, 2022

Missing information? Dealing with missing data.

View Slides

 

November 21, 2022

The right time? Survival analysis.

View Slides

 

November 28, 2022

Who The variety of influences - Mixed models.

View Slides

 

December 5, 2022

Who fits together? Patient matching.

View Slides