Education | Seminar in Logistic Regression
Y750 | 5290 | Peng


Tuesdays 2:30-5:15 p.m.
Education 3284
Joanne Peng (856-8337, PENG@INDIANA.EDU)

Course Comments

1.      The objectives of the course are (1) to gain an
understanding
of some basic features of logistic regression modeling, and
(2) to develop a coherent approach for evaluating the
applications of logistic regression modeling in your
field of study.

2.      Instructions will consist of  lectures, discussions,
computer exercises, and student presentations.

3.      All students will be expected to complete three projects.
The projects are designed jointly by the instructor
and students with an aim to
facilitate student's understanding of various issues

surrounding logistic regression.  The third and final

project will be an in-depth investigation of one or more
issues about logistic regression which the student finds
intriguing.  For this third project, each student will be
given an opportunity to orally present his/her design and
findings in class.

4 .     The primary prerequisite to this course is an equivalent of
a second course in applied statistics which covered
ordinary least squares regression models.  An aptitude for
mathematical analysis and SAS programming is beneficial.
Deficiencies in particular areas will be remedied in
tutorial sessions.

5.      Required texts for the course are
(a) Kleinbaum's Logistic Regression (Springer, 1994),
(b) Demaris' Logit Modeling-Practical Applications
(Sage Publication #86, 1992),
(c) SAS Institute's Logistic Regression:
Examples using the SAS system (SAS Institute, 1995), and
(d) Hosmer and Lemeshow's Applied Logistic Regression
(John Wiley and Sons, 1989).
Additional readings will be announced in class.

Syllabus

Week No.        Topic	

1        Introduction to logistic modeling 	

2 & 3        Fitting the simplest logistic regression model	

4 & 5        Fitting multiple logistic regression model	

6 & 7        Interpreting coefficients of logistic regression	
		models

8 & 9        Assessing the fit of the model	

10 & 11        Model Building strategies and methods

12 & 13        Logistic regression for matched case-control studies	

14         Advanced topic: Polytomous logistic regression	
or
Choosing between logistic regression and discriminant
analysis

15         Student presentations   (none)

Grading System

The final course grade will be a composite of grades assigned to
three
papers students are expected to complete throughout the semester.  Equal
weights
will be applied to the three paper grades in determining the composite.
Specific criteria on paper grades will be announced in class along with
instructions on writing each paper.

Incompletes will be given only for a legitimate reason as outlined
in
the university's Academic Guide, and only after a conference between
the instructor and the student.  Throughout the course of this section,
you may contest every grade awarded to your paper/project or the final
course grade.

Academic Honesty and Intellectual Integrity
	
According to P.72 of the Academic Handbook (June 1992 edition), each
faculty member has "a responsibility to foster the intellectual honesty as
well as the intellectual development of his/her students."  In order to
achieve these goals, each student enrolled in this course is prohibited from
engaging in any form of "cheating" or "plagiarism."  Cheating is defined as
and "dishonesty of any kind with respect to examination, course assignments,
alteration of records, or illegal possession of examinations"  (p. 72 of the
Academic Handbook).  "It is the responsibility of the student not only to
abstain from cheating but, in addition, to avoid the appearance of cheating
and to guard against making it possible for others to cheat.  Any student
who helps another student to cheat is as guilty of cheating as the student
he or she assists.  The student also should do everything possible to induce
respect for the examining process and for honesty in the performance of
assigned tasks in or out of class." (p. 72 of Academic Handbook).

Plagiarism is defined as "offering the work of someone else as one's
own" (p. 72 of Academic Handbook).  "The language or ideas thus taken from
another may range from isolated formulas, sentences, or paragraphs to entire
articles copied from books, periodicals, speeches, or the writings of other
students.  The offering of materials assembled or collected by others in the
form of projects or collections without acknowledgment also is considered
plagiarism.  Any student who fails to give credit for ideas or materials
taken from another source is guilty of plagiarism." (p.72 of Academic
Handbook).

Evidence of student academic misconduct will result in (a) a lowered
course grade, (b) transfer out of this course, (c) dismissal from student's
academic unit, or (d) other disciplinary actions in accordance with the
guidelines outlined on p.73 of Academic Handbook.