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DESCRIPTION:# Overview\nWhile 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
  cannot be analyzed using these simple approaches.\n\nDuring 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-eff
 ects linear models. We will further discuss the application of mixed-effec
 ts linear models in analyzing longitudinal data. Finally\, in an attempt t
 o move beyond linearity\, we will explore extensions of linear models\, su
 ch as polynomial regression\, splines\, local regression\, and generalized
  additive models. Throughout the course\, the emphasis will be put on conc
 rete applications in clinical and biological data analysis using real worl
 d examples.\n\n# Audience\nThis course is intended for life scientists who
  already use the R programming language and have some basic knowledge of s
 tatistics (including statistical tests\, correlation\, and linear models).
 \n\n# Learning outcomes\nAt the end of this course\, participants will be 
 able to:\n*  identify the appropriate model to analyze a dataset\;\n*  fit
  the chosen model using R\;\n*  assess the fit of the model\, as well as i
 ts limitations.\n\n### ***Knowledge / competencies***\nThe course is inten
 ded for people already **familiar with basic statistics and R**. Participa
 nts must be comfortable with topics such as hypothesis testing\, correlati
 on and linear models\, and must have a **prior knowledge of the "R" langua
 ge and environment for statistical computing and graphics**. Participants 
 who have already followed the SIB course ["Introduction to statistics with
  R"](https://www.sib.swiss/training/course/2021-02-intro-stats) or an equi
 valent course\, and have used its content in practice should fit this prer
 equisite.  \n\n**Before applying to this course\, please self-assess your 
 knowledge in stats and R to make sure this course is right for you. Here a
 re 2 quizzes:**  \n- [Quiz: Introduction to Statistics	](https://gohighbro
 w.com/quiz-introduction-to-statistics/)\n	\n- ["Introduction to R" self-as
 sessment for the advanced statistics course](https://docs.google.com/forms
 /d/e/1FAIpQLSfXCnmLha0Ks4ZZZ42G_5MyIbGi-JhPayuHZ_P2jdXZEtXdqg/viewform)\n	
 \n\n\n### ***Technical***\nYou are required to have **your own laptop\, wi
 th at least 4 Gb of RAM\, ["R" v4.2.0](https://www.r-project.org/) and ["R
 Studio" 2022.02.2-485](https://www.rstudio.com/products/rstudio/download/#
 download) software installed**. More information about the packages needed
  will be provided in due time. \n\n# Brief course programme\n*  Monday: si
 mple and multiple linear regression (theory\, diagnostics\, and model sele
 ction)\n*  Tuesday: generalized linear models (binary data\, proportions\,
  and counts)\n*  Wednesday: mixed-effects linear models\, longitudinal dat
 a analysis\n*  Thursday:smoothing and generalized additive models\n\n# App
 lication\nThe registration fees for academics are **400 CHF** and **2000 C
 HF** for for-profit companies.\n\nYou will be informed by email of your re
 gistration confirmation. Upon reception of the confirmation email\, partic
 ipants will be asked to confirm attendance by paying the fees within 5 day
 s.\n\n\nApplications will close as soon as the places will be filled up. D
 eadline for free-of-charge cancellation is set to *21/08/2023*. Cancellati
 on after this date will not be reimbursed. Please note that participation 
 in SIB courses is subject to our [general conditions](http://www.sib.swiss
 /training/terms-and-conditions).\n\n# Venue and Time\nThis course will be 
 held at the University of Lausanne.\n\nThe course will start at 9:00 and e
 nd around 17:00. Precise information will be provided to the participants 
 in due time.\n\n\n#  Additional information\nCoordination: Valeria Di Cola
 \, SIB training group.\n\nWe will recommend 1 ECTS credits for this course
  (given a passed exam at the end of the course).\n\nYou are welcome to reg
 ister 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](
 https://lists.sib.swiss/mailman/listinfo/courses).\n\nPlease note that par
 ticipation in SIB courses is subject to our [general conditions](http://ww
 w.sib.swiss/training/terms-and-conditions).\n\nSIB abides by the [ELIXIR C
 ode of Conduct](https://elixir-europe.org/events/code-of-conduct). Partici
 pants of SIB courses are also required to abide by the same code.\n\nFor m
 ore information\, please contact [training@sib.swiss](mailto://training@si
 b.swiss).
SUMMARY:Advanced Statistics: Statistical Modelling
URL;VALUE=URI:https://www.sib.swiss/training/course/20230904_ASSM
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