Linear Mixed Models for Longitudinal Data,
Spring 2011
Administrative
matters: Contact info, schedule, contents etc
Location: MVF26
Instructors: Ziad
Taib ( 0707655471 ) ziad.taib@astrazeneca.com or ziad@chalmers.se and
Malin Östensson (031 772 53
16) malino@chalmers.se
Textbook:
Linear
mixed models for longitudinal data, Geert Verbeke and
Geert Molenberghs Springer
Verlag, New York plus
some handouts. The exact chapters that are due can be found here.
Exams:
The
Final written exam will be a closed book exam where the necessary complicated
formulas will be provided along with the examination text. No complicated
calculations are required but you might need a simple pocket calculator. Both
“theoretical” and applied problems can be posed. You should be able to
interpret Proc Mixed results but you will not be required to write any code,
SAS or otherwise. Out of a total of 30 (100%) possible scores, the computer
assignments give a “bonus” of up to 6 scores (20%) while the written exam gives
24 scores (80%). There are three possible grades: Excellent (over 26 scores),
Pass (over 16 scores) and do not pass (under 16 scores). Some sample questions
covering parts of the course can be found here. Solutions to these as well as examples of “theory” questions can be
found in the lecture notes below named Repetition as well as some other sample questions. The solutions to the exam can
be found here.
Policy
on Homework:
Computer
Assignments is to be presented in a report, with programs, output, and
statistical notation integrated. The quality of writing and organization, as
well as content, will influence the grade. Homework may be turned in directly
to Malin Östensson. The
deadlines for the assignments are May 9 for lab1 and
May 23 for lab2.
Computer Access:
All
students are supposed to have a computer account. This account will enable
computer lab use and use of computers in the School of Mathematical Sciences.
Software:
This
course will make extensive use of SAS. This software is available on the
computers that will be used. Alternatively, R, Splus
or Spss can be used to solve the home assignments but
no instructions will be given in these programs.
Schedule and Outline of Lectures:
|
April 5 |
Introduction to Linear Mixed Models (Chap
1-4) |
|
April 7 |
Estimation and Inference for the
marginal model (Chap 5-6) |
|
April 19 |
Inference for the random effects,
Software issues (Chap 7-8) |
|
April 26 |
Non-linear and Generalized Linear Mixed
Models (Handouts) |
|
May 3 |
Incomplete data (Chap 15-16) |
|
May 10 |
Design and sample size issues (Chap
23) |
|
May 17 |
Model checking |
|
May 24 |
Examples – Repetition- Sample Exam |
|
Exam |
Computer assignments: