Admission requirements
A basic understanding of introductory statistical concepts and some familiarity with R as taught in Inleiding Mathematische Statistiek.
Description
An overview about each of the three topics presented in this course is given here below
Survival analysis (Prof. dr. M. Fiocco)
This area of statistics deals with time to event data, whose analysis is complicated not only by the dynamic nature of events occurring in time but also by censoring where some events are not observed directly but it is only known that they fall in some interval or range. Different types of censored and truncated data, non-parametric methods to estimate the survival function and regression models to study the effect of risk factors on survival outcomes will be discussed. Special aspects such as time-dependent covariates and stratification will be introduced.
Bayesian methods (Dr. V. Masarotto)
The goal of the four lessons is to give an introduction to Bayes thinking, with some practically motivated examples. The course will provide basis knowledge of Bayesian statistics and (if possible) classic non-parametric estimation within the bayesian framework. We will explore what it means to embrace a bayesian perspective, and then move into introducing some canonical classes of models, covering simple approaches to posterior computation within such models. If time allows, we will discuss what it means to think “non-parametrically” within a Bayesian paradigm. We will include some basic estimations using the R software environment.
Causal inference (Dr. M. Spreafico)
Causal inference is a branch of statistics that deals with understanding the cause-and-effect relationships between variables. These four lessons will provide an overview of concepts and methods for estimating the causal effects of exposures on (time-to-event) outcomes. Topics will include counterfactual outcomess, identifiability assumptions, causal diagrams, time-dependent confounding, inverse probability of treatment weighting, marginal structural models, and the G-formula. After introducing the theory, we will also explore how to formulate causal questions, design studies to answer them, and draw causal inferences from data while considering potential sources of bias. Implementation and estimation will be performed using the R software.
Course Objectives
The overall aim of the course is to introduce students to three different areas of statistics. By the end of the course, students are expected to have a basic understanding of the topics discussed and to be able to use existing software to apply the methods covered during the course.
Timetable
In MyTimetable, you can find all course and programme schedules, allowing you to create your personal timetable. Activities for which you have enrolled via MyStudyMap will automatically appear in your timetable.
Additionally, you can easily link MyTimetable to a calendar app on your phone, and schedule changes will be automatically updated in your calendar. You can also choose to receive email notifications about schedule changes. You can enable notifications in Settings after logging in.
Questions? Watch the video, read the instructions, or contact the ISSC helpdesk.
Note: Joint Degree students from Leiden/Delft need to combine information from both the Leiden and Delft MyTimetables to see a complete schedule. This video explains how to do it.
Mode of Instruction
Weekly 2 × 45 min of lecture in class, and 2 × 45 min of practical sessions with exercises. Laptop with the statistical package R (http://www.r-project.org) already installed is required for each practical section.
Assessment method
Three individually written reports (25% each), and a presentation (25%) on a selected topic. The presentations will be held individually or in pairs, depending on the group size. The reports are regarded as practical assignments, and can not be retaken. The presentation can be retaken.
Reading list
Lecture material and references provided in class.
Registration
As a student, you are responsible for enrolling on time through MyStudyMap.
In this short video, you can see step-by-step how to enrol for courses in MyStudyMap.
Extensive information about the operation of MyStudyMap can be found here.
There are two enrolment periods per year:
Enrolment for the fall opens in July
Enrolment for the spring opens in December
See this page for more information about deadlines and enrolling for courses and exams.
Note:
It is mandatory to enrol for all activities of a course that you are going to follow.
Your enrolment is only complete when you submit your course planning in the ‘Ready for enrolment’ tab by clicking ‘Send’.
Not being enrolled for an exam/resit means that you are not allowed to participate in the exam/resit.
Contact
Please see Brightspace for more information
Remarks
Software
Starting from the 2024/2025 academic year, the Faculty of Science will use the software distribution platform Academic Software. Through this platform, you can access the software needed for specific courses in your studies. For some software, your laptop must meet certain system requirements, which will be specified with the software. It is important to install the software before the start of the course. More information about the laptop requirements can be found on the student website.