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·        Course requirements and goals

MSA650, Linear Mixed Models for Longitudinal Data, Spring 19

  Latest news

   Welcome to the course! The schedule for the course can be found in TimeEdit.

Teachers

Course coordinator: Ziad Taib (ziad@chalmers.se) phone: +46 707 65 54 71.

Teachers: Ziad Taib and José Sanchez (jose.sanchez1@astrazeneca.com).

Teaching assistant: Juan Inda (inda@chalmers.se)

Lab supervisor: Juan Inda and Mahdi Hashemi (mahdi.hashemi@astrazeneca.com)

Course literature

   Linear mixed models for longitudinal data, Geert Verbeek and Geert Molenberghs, Springer Verlag, New York plus some handouts.

Program

Lectures

January 23

Introduction (Chap 1-4) ZT

January 25

Estimation for the marginal model (Chap 5) JS

January 30

Inference for the marginal model (Chap 6) JS  

Computer Project

February 1

Inference for the random effects (Chap 7) JS 

February 8

Fitting mixed models (Chap 8 plus lecture notes) JS 

February 13

Generalized Linear Mixed Models (Handouts) ZT

Computer Project 

February 15

Non-linear Mixed Models (Handouts) ZT 

February 20

Incomplete data (Chap 15-16) ZT

Computer Project

February 27

Imputation in Mixed Models (Handouts) ZT

March 1

Design and sample size issues (Chap 23) ZT

Computer Project

March 4

Model checking (Handouts) ZT 

March 6

Reserv ZT and JS

Computer Project

March 8

Repetition ZT and JS

 

 

Reading Instructions        

Chapters 1-5

The whole chapter is required

Chapter 6

6.1 to 6.3.3

Chapter 7

7.1-7.7

Chapter 8

The whole chapter is required

Chapter 14

Self-reading

Chapter 15

The whole chapter is required

Chapter 16

The whole chapter is required

Chapter 20

20.3

Chapter 23

The whole chapter is required

Handouts

Generalized mixed models

Handouts

Non-linear mixed models

Handouts

Model checking

 

Computer labs

   The computer projects will take place on the following dates: 30/1, 13/2, 20/2/, 27/2 and 6/3.

   Reference literature:

   Linear mixed models for longitudinal data, Geert Verbeek and Geert Molenberghs, Springer Verlag, New York plus some handouts.

Course requirements and goals

    Pre-requisites: Some course in experimental design and familiarity with regression analysis.

 

    Course Objectives: The purpose of this course is to give an introduction to mixed model methods and longitudinal data analysis. Non-linear models and generalized models will also be touched upon briefly. The course aims to enable the participants to formulate a mixed model, define and interpret possible estimators, and implement a mixed model analysis for a two-stage nested study, a repeated measures study, and a factorial experimental study. More specifically the participant will be able to

 

Assignments

    Cf. Computer projects.

Examination

Grading: Computer Projects: 20%, Final written exam: 80% (cf. below)  

Rules: A closed book exam which means that no material is allowed other than a simple pocket calculator.

Scores: The written exam is worth 24 scores (80%) while the computer assignments are worth 6 scores (20%). Together these two parts add up to 30 scores (100%). There are three possible overall grades: Excellent (at least 26 scores), pass (at least 16 cores) and do not pass (less than 16 cores).        

 More information on the final exam will be a given later.

Examination procedures

In Chalmers Student Portal you can read about when exams are given and what rules apply on exams at Chalmers. In addition to that, there is a schedule when exams are given for courses at University of Gothenburg.

Before the exam, it is important that you sign up for the examination. If you study at Chalmers, you will do this by the Chalmers Student Portal, and if you study at University of Gothenburg, you sign up via GU's Student Portal, where you also can read about what rules apply to examination at University of Gothenburg.

At the exam, you should be able to show valid identification.

After the exam has been graded, you can see your results in Ladok by logging on to your Student portal.

At the annual (regular) examination:
When it is practical, a separate review is arranged. The date of the review will be announced here on the course homepage. Anyone who can not participate in the review may thereafter retrieve and review their exam at the
Mathematical Sciences Student office. Check that you have the right grades and score. Any complaints about the marking must be submitted in writing at the office, where there is a form to fill out.

At re-examination:
Exams are reviewed and retrieved at the
Mathematical Sciences Student office. Check that you have the right grades and score. Any complaints about the marking must be submitted in writing at the office, where there is a form to fill out.

Old exams

The questions and solutions from the exam in June 2019. More are available on Drive.