Advanced Statistics: Statistical Modelling

The course is now full with a long waiting list. If you do not want to miss your chance to be part of the next session and remain informed about all training activities at SIB, we highly recommend you to keep an eye on our list of upcoming events (https://www.sib.swiss/training/upcoming-training-courses) and subscribe to our courses mailing list here (if not yet done): https://lists.sib.swiss/mailman/listinfo/courses. Thank you for your understanding.

Overview

While the statistical models and tools presented in an introductory statistics course (such as linear regression) can be used to answer a wide range of questions in life sciences, many types of data can not be analyzed using these simple approaches.

During this course, we will discuss statistical models and techniques beyond classical linear modelling. Following a brief review of the basics of linear regression, we will dive into more advanced topics, such as generalized and mixed-effects linear models. We will further discuss the application of mixed-effects linear models in analyzing longitudinal data. Finally, in an attempt to move beyond linearity, we will explore extensions of linear models, such as polynomial regression, splines, local regression, and generalized additive models. Throughout the course, the emphasis will be put on concrete applications in clinical and biological data analysis using real world examples.

Audience

This course is intended for life scientists who already use the R programming language and have some basic knowledge of statistics (including statistical tests, correlation and linear models).

Learning outcomes

At the end of this course, participants will be able to:

• identify the appropriate model to analyze a dataset;
• fit the chosen model using R;
• assess the fit of the model, as well as its limitations.

Prerequisites

Knowledge / competencies

The course is intended for people already familiar with basic statistics and R. Participants must be comfortable with topics such as hypothesis testing, correlation and linear models, and must have a prior knowledge of the "R" language and environment for statistical computing and graphics. Participants who have already followed the SIB course "Introduction to statistics with R" or an equivalent course, and have used its content in practice should fit this prerequisite.

Before applying to this course, please self-assess your knowledge in stats and R to make sure this course is right for you. Here are 2 quizzes:
https://gohighbrow.com/quiz-introduction-to-statistics/
https://docs.google.com/forms/d/e/1FAIpQLSfXCnmLha0Ks4ZZZ42G_5MyIbGi-JhPayuHZ_P2jdXZEtXdqg/viewform

Technical

You are required to have your own laptop, with at least 4 Gb of RAM, "R" v4.03 and "RStudio" v1.4.1717 software installed. More information about the packages needed will be provided in due time.

Brief course programme

• Monday: simple and multiple linear regression (theory, diagnostics, and model selection)
• Tuesday: generalized linear models (binary data, proportions, and counts)
• Wednesday: mixed-effects linear models, longitudinal data analysis
• Thursday:smoothing and generalized additive models

Application

We are sorry but this course is oversubscribed, with a long waiting list. Application is therefore closed.

The registration fees for academics are 240 CHF and 1200 CHF for for-profit companies.

You will be informed by email of your registration confirmation. Upon reception of the confirmation email, participants will be asked to confirm attendance by paying the fees within 5 days.

Applications will close as soon as the places will be filled up. Deadline for free-of-charge cancellation is set to 23 July 2021. Cancellation after this date will not be reimbursed. Please note that participation to SIB courses is subject to this and other general conditions, available here.

Venue and Time

This course will be streamed from Lausanne.

The course will start at 9:00 CET and end around 17:00 CET. Precise information will be provided to the participants in due time.

Additional information

Coordination: Diana Marek

We will recommend 1 ECTS credits for this course (given a passed exam at the end of the course).

You are welcome to register to the SIB courses mailing list to be informed of all future courses and workshops, as well as all important deadlines using the form here.

Please note that participation in SIB courses is subject to our general conditions.

SIB abides by the ELIXIR Code of Conduct. Participants of SIB courses are also required to abide by the same code.

For more information, please contact training@sib.swiss.