• Start date:
  • 4 March 2024
  • Duration:
  • 5 days
  • Intended Audience:
  • Researcher, PhD

Introduction

The course discusses the objectives and methodological foundations of a number of commonly used regression methodologies in biomedical research from a practical perspective. In short: what is regression (in terms of assumptions made on data), what is it for (which objectives), when can we use it (or not), how can we interpret results from it (and when not).

It is important to understand that while the course has an applied flavor and aims to instill a greater awareness of the nature and uses of regression methodology in practical research, it does not teach or instruct on fully worked out analysis plans. That would be impossible to achieve in any case, given the huge diversity of regression applications in biomedical research. Neither is the course a fully-fledged theoretical statistics instruction on regression methods, nor does it aim to teach regression software.

Instead the courses teaches the general knowledge of regression methodology that can be combined in real-life research to answer questions you may have.

The focus is on linear and logistic regression models, although other models, like Poisson models or non-linear regression models for continuous data will also be discussed.

Included topics are: simple linear regression, multiple linear regression, variance and covariance analysis (using a regression approach), adjustments for confounding, interaction, polynomial and other non linear regression models, logistic regression, goodness-of-fit, multivariate modeling, conditional logistic regression, generalized linear regression models, and the building of prediction models.

Course material
All study materials are supplied electronically only in the Boerhaave Learning Environment, and will be made available partially before, and partially during the course. 

Prerequisites
Basic knowledge of statistics is required (equivalent to the Boerhaave course "Basic methods and reasoning in Biostatistics"). Students are highly recommended to follow the Regression Analysis course, before proceeding with the more advanced ‘Analysis of Repeated Measurements’ course.

A computer / laptop with proper internet access for all participants is mandatory. All statistical methods are practiced, using SPSS (recommended software). Students should have access to latest version of SPSS. Using other software is possible, but no support will be provided for this during the course.

Teaching environment
The course consists of daily, online self-study hours with video's and practical exercises, and on campus plenary Q&A sessions and discussions with the teacher.  At the end of each day, solutions from the practical assignments are discussed during a general session of approximately one hour. 

Certificate of attendance
In order to obtain a proof of participation, it is mandatory to attend the introduction on Monday and all daily Q&A sessions and plenary discussions. In addition, all practical assignments should be completed. If you have participated in the full course, you will receive a certificate of attendance within two weeks. Completing a post-course assignment is required to complete the course. This assignment will be graded with a 'pass' or 'fail'.  ECTS: 1,5. 

Language
Course material and lecture video's are all in English. 

Target group
Master and PhD students in the bio-medical sciences.

Organizing committee

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* Interested in another statistics course? Please visit our website to check out the various courses that are offered by Boerhaave Nascholing.

  CONCEPT PROGRAMMA
  MONDAY 04 MARCH 2024 (DAY 1)
Morning  Self-study / Lecture video's (own workplace)
13:00 Introduction to course, Q&A session about video content day 1 + introduction practical exercise
Dr. B.J.A. Mertens
Lecture Hall 3, LUMC
14:00 Self-study / Practical exercise
Own workplace     
16:30 Plenary discussion 
Dr. B.J.A. Mertens
Lecture Hall 3, LUMC
17:30        End of course day
   
  TUESDAY 05 MARCH 2024 (DAY 2)
Morning    Self-study / Lecture video's (own workplace)
13:00 Q&A session about video content day 2 + introduction practical exercise
Dr. B.J.A. Mertens
Lecture Hall 3, LUMC
14:00 Self-study / Practical exercise
Own workplace     
16:30 Plenary discussion
Dr. B.J.A. Mertens
Lecture Hall 3, LUMC
17:30 End of course day
   
  WEDNESDAY 06 MARCH 2024 (DAY 3)
Morning   Self-study / Lecture video's (own workplace)
13:00 Q&A session about video content day 3  + introduction practical exercise
Dr. B.J.A. Mertens
Lecture Hall 3, LUMC
14:00 Self-study / Practical exercise
Own workplace    
16:30 Plenary discussion
Dr. B.J.A. Mertens
Lecture Hall 3, LUMC
17:30 End of course day
  THURSDAY 07 MARCH 2024 (DAY 4)
Morning  Self-study / Lecture video's (own workplace)
13:00 Q&A session about video content day 4  + introduction practical exercise
Dr. B.J.A. Mertens
Lecture Hall 3, LUMC
14:00 Self-study / Practical exercise
Own workplace 
16:30 Plenary discussion 
Dr. B.J.A. Mertens
Lecture Hall 3, LUMC
17:30        End of course day
   
  FRIDAY 08 MARCH 2024 (DAY 5)
Morning    Self-study / Lecture video's 
Own workplace
13:00 Q&A session about video content day 5 + introduction post-course assignement
Dr. B.J.A. Mertens
Lecture Hall 3, LUMC
14:00 End of course 
A post-course assignment (exercise day 5) will be published in de learning environment.
Deadline for sending in results: Sunday 24 March 2024
Dr. B.J.A. Mertens
LUMC
Albinusdreef 2, 2333 ZA Leiden

Building: Gebouw 1
Route: 764
Room: Collegezaal-3

Route description to the LUMC and parking

Regular course fee € 950,-
Reduced fee for PhD students LUMC  € 195,-
Reduced fee for employees LUMC € 195,-
BA/MA students of the Leiden University  Free of charge *
Students of other universities (non Leiden University)        € 79,- *

* Limited places available. In order to validate your student registration, you must register with your student e-mail address and submit your student number on the registration form. In addition, a scan of your student pass will have to be submitted to boerhaavenacholing@lumc.nl. Please note that a € 50,- cancellation fee will be charged to students who do not attend the course (no show), or cancel their registration. Incomplete registration will not be considered.

Please note that upon registration, you agree to our Terms and Conditions, including the stated cancellation policy. Administration fees may be charged upon cancellation.