Study unit
3622350 Analysis of grouped data, 5 Cp  
Code 3622350  Validity 01.01.1950 -
Name Analysis of grouped data  Abbreviation RAA 
Credits 5 Cp Date of expiry  
TypeIntermediate Studies Subject0390 Statistics 
ClassStudy Unit  Hours  
Study right   Grading0-5 
Recommended scheduling 
   
Organisation Computer Science (J,K) 

Description
Learning outcomes 

To understand the special properties of grouped datasets from modeling point of view. To be able to model such datasets using theoretically justified means.

 
Content 

Linear mixed-effects models provide extension of linear models into such grouped datasets, where observations within the group are correlated. Examples about such datasets are pupils within school class, trees on a forest sample plot, and repeated measurements of persons. Essentially, the groups (school classes, sample plots, persons) are a sample from a population of groups. The course covers linear mixed-effects models with one level of hierarchy. At the end of the course, we will discuss about extensions to more complicated groupings, such as nested groupings and crossed groupings. Lectures in English.

 
Modes of study 

Exercises and exam

 
Teaching methods 

Multi-modal teaching. Lectures (2 h), tutorials (16 h). Student prepares for the weekly tutorials by reading given material, watching videos at moodle, and working on the weekly exercises. In the tutorials, the student has a possibility to make questions on weekly topics and exercises. After the tutorials, the solutions are returned in Moodle, and students do a self-evaluation of them based on given instructions.

 
Study materials 

Lecture notes.  Pinheiro and Bates 2000. Mixed-effects models in S and S-Plus. Springer. Available at UEF library in electronic form. Stroup, W. 2013. Generalized linear Mixed models. Modern concepts, methods and applications. CRC Press. Galecki and Burzykowski. Linear mixed-effects models using R : a step-by-step approach. Springer, 2013.

 
Evaluation criteria 

0-5

 
Prerequisites 

Data analysis or Regression analysis 1 and 2, R-course

 


Letter (J, K) in front of the name of the course/exam indicates the campus on which teaching or exam takes place: J = Joensuu, K = Kuopio.

Present and future teaching
Functions Name Type Cp Teacher Timetable
Registration ended
(JOENSUU): Analysis of grouped data  Multi-modal teaching  Lauri Mehtätalo  17.03.20 -12.06.20
Registration ended
(KUOPIO): Analysis of grouped data  Multi-modal teaching  Lauri Mehtätalo  17.03.20 -12.06.20

Future exams
Functions Name Type Cp Teacher Timetable
Registration not started (JOENSUU): Analysis of grouped data  General examination  Lauri Mehtätalo 
20.08.20thu 12.00-16.00
Registration not started (KUOPIO): Analysis of grouped data  General examination  Lauri Mehtätalo 
20.08.20thu 12.00-16.00