UNIVERSITY OF
DEPARTMENT OF FOOD
AND RESOURCE ECONOMICS
STAT616 ¾ Advanced Design of Experiments
Fall 2011
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Instructor: John D. Pesek, Jr.
227 Townsend
Hall
302-831-1319
E-mail:
pesek@udel.edu
Web site
http://www.udel.edu/pesek/index.html
007 Townsend
Hall
Office
Hours: By
appointment
Texts: Required: SAS System for Mixed Models,
Second Edition, Littell, Milliken, Stroup, Wolfinger and Schabenberger, SAS
Institute,
Prerequisites: STAT615 and STAT602
Objective: Study the design and analysis of mixed
and repeated measures models using the mixed procedure of SAS along with
related topics.
UNIVERSITY OF DELAWARE GENERAL
EDUCATION GOALS: The objectives of this
course align with the following General Education Goals (bolded):
Attain effective skills in (a) oral and (b) written communication,
(c) quantitative reasoning, and (d) the use of information technology – By
doing homework assignments, supportive reading and lab exercises. This involves
analysis and computation, both by hand and using SAS software.
Learn to think critically to solve problems – By doing homework
assignments and lab exercises. Both involve analysis and computation, both by
hand and using SAS software.
Be able to work and learn both independently and
collaboratively – By doing independent homework
assignments and lab exercises in
collaboration with a partner. Both involve analysis and computation, both by
hand and using SAS software.
Course
Requirements:
1. The dates of the exams and other parts of the course are
subject to change in the light of weather related and other contingencies.
2. On Tuesday, October 18, 2011 there will
be a midterm examination for the first 120 minutes of the course. There will
also be a final at a date to be announced. Important! The final and
midterm must be taken at the scheduled time unless prior arrangements are made.
There must be adequate cause in the judgment of the instructor.
Note: Plane
reservations leaving before the final date are not considered adequate cause.
Note: Attendance at a wedding is not adequate
cause for taking exams at other times. This is regardless of whether you are
getting married, you are a member of the wedding party, or you are just in
attendance.
Note: Having more than one final on the same day is
also not adequate cause.
Note:
There are many legitimate reasons such as illness and family emergencies.
Please contact me under those circumstances.
Note:
Students with either learning and/or physical disabilities are entitled to
special consideration according to university policy. To qualify for this
consideration, the instructor must be given official notification of the
disability from the appropriate university unit.
Both the midterm
and the final will be cumulative.
Some questions on the exam will require the demonstration of lessons
learned in class and in the homework while some will also require the
resourceful use of that knowledge. When
preparing for exams, it is important to remember that in addition to using the
skills acquired in class, it is also necessary to be able to decide which
skills are needed for a particular problem.
I often give out
practice exams. The primary purpose of the practice exam is to give you a
chance to see the general structure of my exams. There is no guarantee that the
questions will be the same or similar to questions on the practice exams.
3. There are a number of required
assignments. Each assignment is due on a specific date to be announced. All
assignments will be graded on the basis of content and presentation. Any
assignment that is turned in after the due date without a proper excuse will
receive a score of zero. In general assignments will be submitted using
Sakai.
4. There will generally be at least one
laboratory exercise per class. In general these will be done in pairs. The
purpose is to give you a chance to learn by doing. Credit is given for
participation. In case an exercise is missed, students with a proper excuse
will have their grade based on other work done. Otherwise a grade of zero will
be recorded. Students are held responsible for all work covered and for meeting
course deadlines. In general the lab exercise is due by 1:30pm the Thursday
after class.
Note: Missing class in order to complete work
for another class or to study for an exam in another class is not a
proper excuse.
5. During class students are expected to
be respectful of each other and the instructor. It is especially important to
respect your lab partner. Questions are welcome if they are germane to the
current topic. Other questions are welcome when asked in private. In this class
data will come from a variety of disciplines. It is natural to be most
interested in data from your own field of study. However, respect and courtesy
toward data from other disciplines are expected.
6. Academic honesty is expected at all
times (See the Student Guide to
University Policies for complete information on the Code of Student
Conduct at http://www.udel.edu/stuguide/11-12/index.html
).
7. The computer labs and classroom do not
allow food, coffee or beverages at all times. The one exception for classroom
use only is that water is allowed in bottles with caps. The water bottles must
be kept away from the computers when not in use.
8. In general students are expected to
know and follow the computer lab rules as well as the university's policy on
responsible computer use.
Grading
Procedure:
The final course grade will be based upon the student’s
performance on the assignments and the exams. The assignments will count 25-35
percent of the grade and the exams 65-75 percent of the grade.
Important information for listeners (official auditors). At
the University of Delaware you may take a course as a listener. Then you are
not required to take exams or turn in homework although you may do so. However,
you ARE required to attend class. If a student has listener status and has a
large number of unexcused absences, the instructor may give a grade of LW (for
listener withdrawn) instead of L (for listener). While an LW will not affect your GPA or your
graduation, prospective employers are often concerned to see withdrawn courses
on your transcript and it is best to avoid them.
Requests
for score changes:
If you feel either an assignment or an exam deserves a
higher score, you need to make a written request. The written request must be
made on a separate sheet of paper
and the assignment or exam must be attached. If you are still not satisfied,
you may make an appointment with the instructor to discuss the matter. For Sakai
assignments written requests may be made by the Sakai message system. In this case there will be no need to include
the assignment since I will have retained a copy.
Consultations:
Students are encouraged to visit the instructor in his
office. Students may make appointments or drop by (in the last case the
instructor may not always be available).
Students are also encouraged to communicate with the instructor using
E-mail.
Announcements:
Announcements about the course will be made by e-mail.
Students should pay close attention to e-mail messages from the instructor.
Handouts:
In general handouts
will be available on Sakai in “pdf” format. Students are expected to download
and print copies to have available in class.
Some handouts may still be provided in class. To access the handouts go
to the URL
http://www.udel.edu/sakai
and log onto Sakai. Then go to stat616.
It is important to make every effort to print the
handouts before class. The computer lab printer will not print fast enough if
everyone prints the handouts at class time.
This semester we
will be using Sakai for submission of assignments as well as grading.
Topics
to be covered (depending on time and interest of the class) are:
¨
Review of design principles
à
Using tree diagrams to understand
designs
à
Contrasts
¨
Introduction to mixed models and
repeated measures.
à
Fixed and random effects
à
Repeated measures with patterned
covariance matrices
¨
"Classical" Approaches to
repeated measures (Greenhouse-Geisser and Huhyn-Feldt methods)
¨
The mixed model equations
¨
Satterthwaite and Kenward-Rogers
degrees of freedom
¨
BLUEs (Best Linear Unbiased Estimators)
for fixed effects
¨
BLUPs (Best Linear Unbiased Predictors)
for random effects
¨
Generalized linear mixed models
¨
Power
¨
Randomization
¨
Examples such as
à
Block designs
à
Split plot and split-split plot designs
à
Longitudinal studies
à
Latin squares
à
Analysis of Covariance
à
Random Coefficient Models
¨
Other topics such as non-linear mixed
models may be covered if time permits.