• Start date:
  • 2 February 2021
  • Duration:
  • Working as:
  • PhD

The course consists of e-learning modules, online ‘live’ lectures, short videos and online question hours.

The LUMC course ‘Basic Methods and Reasoning in Biostatistics’ covers the fundamental toolbox of biostatistical methods plus a solid methodological basis to properly interpret statistical results. The course is a mandatory part of the LUMC Graduate School Program and a prerequisite for any of the advanced biostatistical courses offered by the LUMC. This is a basic course, which targets a wide audience. The course is planned for a single week (+ preparation in the two weeks before), followed by a final examination on the next Tuesday.

Each day we start with an on-line lecture in Zoom, followed by a question hour for discussing questions on the e-learning. The rest of the day participants work individually through the e-learning.

The lectures cover the 'Reasoning' part of the course. Three lectures are mandatory: Study design, Good statistical practice and Multiple testing. Moreover, we offer two elective lectures: for participants interested on this topic, we offer an advanced elective lecture on modern prediction techniques. Also, since many of the examples during the course stem from clinical research, one elective lecture dedicated to pre-clinical research is offered. The lecture slides as well as additional lecture materials will be made available electronically at the end of the course (check the 'lectures' folder at the Section 'Course material').

In the short videos (about 10 minutes each), several experts discuss further on the 'reasoning' topics such as study design, bias, p-hacking, publication bias, good statistical practice, sample size calculation, pros and cons of p-values. In the e-learning part of the course, we will cover the basic methods of data description and statistical inference (t-test, one-way ANOVA and their non-parametric counterparts, chi-square test, correlation and linear regression, logistic regression, introduction to survival analysis and introduction to repeated measurements). For participants who are new to data analysis, the e-learning offers step-by-step guidance on how to perform these procedures in SPSS. Participants who are used to working with R can do the exercises in R instead of SPSS (note that answer models for R are offered but not step-by-step guidance for R starters). Participants who have already studied the e-learning topics in previous courses can use the e-learning as a refresher and work through the modules more quickly skip exercises if wanted. An online forum is available within the e-learning for posing questions during the full week and during preparation.

You will get access to the e-learning modules by January 25th. You are advised to work through the first 5 modules of the e-learning before the official start of the course on February 8th.

Make sure you have either SPSS or R (according to your preference) installed on your computer to work through the e-learning. You can find an SPSS trial version at https://www.ibm.com/analytics/spss-trials. R is a free software environment and can be downloaded from the R project website. Contact the ICT department if you need help with the installation.

Prerequisites

  • Secondary school mathematics. No prior knowledge of biostatistics required.

Preparation

You will get access to the e-learning modules around January 25th. You are advised to work through the first 5 modules of the e-learning before the official start of the course on February 8th.

Teaching environment

  • On-line live lectures, short videos and e-learning including practical sessions with SPSS or R.

Recommended book

  • Aviva Petrie & Caroline Sabin (for reference purposes only; not used during course)
    Medical Statistics at a Glance.
    ISBN 0-632-05075-6

Exam

  • The exam assesses your knowledge of the topics discussed in the course (mostly elearning but also few questions about the short videos)
  • The exam will take place on Tuesday 16 February 2021.
  • You can make the exam from home

For more information

  • Please see this introductory video about the course: video

Concept programm

  Monday 2 - 6 February 2021
  Self-study online e-learning part 1 - 5
   

 

Monday 8 February 2021
09:00 Registration: Lecture hall 4
09:30 Introduction
10:30 Break
10:45 Design
11:45 E-learning Descriptive Statistics
17:00 Finish e-learning
   
  Tuesday 9 February 2021
09:00 Question session
09:30 Distributions and bootstrap
10:30 Break
10:45 DAG's and Bias I
11:45 E-learning Principles of statistical testing
17:00 Finish e-learning
   
  Wednesday 10 February 2021
09:00 Question session
09:30 Good Statistical Practice
10:30 Break
10:45 Multiple testing
11:45 E-learning Comparing numerical varaibles
17:00 Finish e-learning
  Thursday 11 February 2021
09:00 Question session
09:30 Bias II and III
10:30 Break
10:45  Sample size calculation
11:45 E-learning Comparing categorical variables
17:00 Finish e-learning
   
  Friday 12 February 2021
09:00 Question session
09:30 Hypothesis testing recap
10:30 Break
10:45 Hypothesis testing revisited
11:45 E-learning Linear regression and correlation
17:00 Finish e-learning
   
  Tuesday 16 February 2021
09:00 Exam
18:00 Closing
Dr. N. van Geloven
Leids Universitair Medisch Centrum (LUMC)
Dr. M.D.M. Rodríguez-Girondo
Leids Universitair Medisch Centrum (LUMC)
Online
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Participation fee for employees LUMC/PhD Students    €  150

Participation fee outside LUMC                                      €  950

Bachelor/master students of the Leiden University are free of charge**  
**Participation is free of charge for bachelor and master students of the Leiden University but only when you fill in your student email address and your student number. Please be informed that we have limited places available for students because this course is mandory for PhD Students. 

Please be informed that we can ask you to show your student pass at registration.

Please note that a fee will be charged to LUMC students who do not attend courses or who are too late with cancelling their participation of the course.

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