TILS2300 Mixed Models and Longitudinal Data Analysis (2–5 cr)
Study level:
Advanced studies
Grading scale:
0-5
Language:
Finnish
Responsible organisation:
Department of Mathematics and Statistics
Curriculum periods:
2024-2025, 2025-2026, 2026-2027, 2027-2028
Description
The course is a continuation for the YLM1 and YLM2 courses. The course introduces methods that can be applied in situations where the data contains correlated observations (clustered observations, repeated measurements, data from longitudinal studies, spatial data, etc.). The most important methods are mixed models and generalized estimating equations (GEE). The course covers the basic theory of methods (definition of models, estimation of parameters, prediction, testing). The applications to various data types are practiced using R software. If the schedule allows, in addition to the methods mentioned above, the analysis of longitudinal data using transition models will be considered.
Learning outcomes
A student who has successfully completed the course:
- knows the basic theory behind the methods: knows how to define the models and list the assumptions; knows the most important estimation and predicting techniques,
- can choose a suitable model for data at hand and fit the model with R software; can perform model diagnostics,
- can make conclusions based on the statistical analysis and report the results.
In addition, degree students in statistics and data science master the theory related to the discussed methods.
Additional information
Degree students in statistics and data science take the 5 ECTS course. Degree students from other fields can take either 3 ECTS course or 5 ECTS course.
The course will be lectured every 1,5 years or more often.
Description of prerequisites
5 ECTS course: Statistical inference 1 and 2, Generalized linear models 1 and 2
2 ECTS course: From data to model, basic knowledge of R software. Generalized linear models 1 (5 ECTS) is highly recommended.
Completion methods
Method 1
Evaluation criteria:
Arviointiin vaikuttavat menestys kurssitentissä ja mahdollisesti aktiivisuus harjoitustehtävien tms. tekemisessä sekä harjoitustyöstä suoriutuminen.
Select all marked parts
Method 2
Evaluation criteria:
Kurssin lopputentissä hyväksyttyyn suoritukseen vaaditaan yleensä vähintään puolet tentin maksimipisteistä.
Select all marked parts
Parts of the completion methods
x
Teaching (2–5 cr)
Type:
Participation in teaching
Grading scale:
0-5
Language:
English, Finnish
Teaching
10/28–12/20/2024 Lectures
12/18–12/18/2024 Course Exam
1/17–1/17/2025 Exam
x
Exam (2–5 cr)
Type:
Exam
Grading scale:
0-5
Language:
Finnish