Graduate Studies Reports Access
Graduate Course Proposal Form Submission Detail - PHC7017
Tracking Number - 2865
Edit function not enabled for this course.
Current Status:
Approved by SCNS - 2012-06-15
Campus: Tampa
Submission Type: New
Course Change Information (for course changes only):
Comments: To GC Chair 5/4/12 for MPH Epi Conc; GC appd 5/15/12. to USf 5/15/12. pending conf of pre-req. PHC 6055 doesn't exist. Corrected to HSC 6055. Cleared. Approved eff 8/1/12
Detail Information
- Date & Time Submitted: 2012-03-26
- Department: Epidemiology and Biostatistics
- College: PH
- Budget Account Number: 640300-10000-PUB001-0000000
- Contact Person: Wendy Nembhard
- Phone: 8139746861
- Email: wnembha@health.usf.edu
- Prefix: PHC
- Number: 7017
- Full Title: Epidemiology Methods IV
- Credit Hours: 3
- Section Type: C -
Class Lecture (Primarily)
- Is the course title variable?: N
- Is a permit required for registration?: Y
- Are the credit hours variable?: N
- Is this course repeatable?:
- If repeatable, how many times?: 0
- Abbreviated Title (30 characters maximum): Epidemiology Methods 4
- Course Online?: C -
Face-to-face (0% online)
- Percentage Online: 0
- Grading Option:
R - Regular
- Prerequisites: PHC 6000, PHC 6010, PHC 6011, PHC 6016 and HSC 6055 or instructor consent
- Corequisites: None
- Course Description: This course builds upon material presented in the Epidemiology Methods course sequence and covers advanced epidemiologic methods, including the epidemiologic perspective of advanced statistical techniques and their proper epidemiologic interpretation.
- Please briefly explain why it is necessary and/or desirable to add this course: Needed to compete with national trends
- What is the need or demand for this course? (Indicate if this course is part of a required sequence in the major.) What other programs would this course service? This course is necessary to fulfill discipline specific competencies and also to ensure that our students can compete with graduates from other Epidemiology doctoral programs.
- Has this course been offered as Selected Topics/Experimental Topics course? If yes, how many times? No
- What qualifications for training and/or experience are necessary to teach this course? (List minimum qualifications for the instructor.) 1) PhD in Epidemiology from accredited institution
2) Knowledge of advanced modeling techniques, statistical assessment of bias, statistical approaches to handling missing data and meta-analyses.
- Objectives: The objective of this course is to provide students with training in advanced epidemiologic techniques.
- Learning Outcomes: By the completion of the course, the students will be able to:
1. Describe and discuss the appropriate use of modeling and modeling techniques
2. Generate causal models and interpret results from models
3. Describe and discuss appropriate approaches for handling the multiple comparisons
4. Describe and discuss the appropriate approaches for sensitivity analyses
5. Conduct sensitivity analyses and their interpret results
6. Describe and discuss the appropriate approaches for handling multiple biases in epidemiologic studies
7. Describe and discuss the appropriate approaches for handling missing data in epidemiologic analyses
8. Use various techniques to conduct data analyses with missing data and appropriately interpret the results
9. Describe and discuss the appropriate approaches for conducting meta-analyses
10. Use various techniques to conduct meta-analyses and appropriately interpret the results
- Major Topics: 1) Advanced modeling in Epidemiology;
2) Multiple Comparisons;
3) Bias;
4) Missing Data; and
5) Meta-Analysis;
- Textbooks: 1) Rothman KJ, Greenland S, and Lash TL. (2008). Modern Epidemiology 3rd edition, Lippincott Williams & Wilkins Press, Philadelphia.
2) Course readings can be downloaded via the Universities Library system or from the course website.
- Course Readings, Online Resources, and Other Purchases: A list of required course readings will be posted on the course management website.
- Student Expectations/Requirements and Grading Policy: Homework Assignments (50% of final grade)
There are 5 homework assignments for this course. These assignments are designed to give you an opportunity to master the concepts covered during class. You will need access to SAS software or another statistical software package of your choice. Refer to the detailed instructions posted on Blackboard.
A. Modeling Assignment I (10%)
B. Modeling Assignment II (10%)
C. Assessing Bias in Epidemiologic Studies (10%)
D. Missing Data Assignment (10%)
E. Meta-analysis Assignment (10%)
Mid-Term Examination (25% of final grade)
The mid-term examination will cover all course material covered from Weeks 1 - 8. Course readings, lectures, discussions, and exercises will all be examined. The exam will be rigorous, closed-book, and will include predominantly short answer and essay questions. Quantitative questions requiring calculations may be included.
Final Examination (25% of final grade)
The mid-term examination will cover all course material covered from Weeks 10-15. Course readings, lectures, discussions, and exercises will all be examined. The exam will be rigorous, closed-book, and will include predominantly short answer and essay questions. Quantitative questions requiring calculations may be included.
STUDENT EXPECTATIONS: 1) Assignments: All assignments must be turned in on time through SafeAssignment in Blackboard.
2) Assignment Due Dates: Assignments are expected to be turned in by being uploaded into Blackboard through Safe Assign not later than11:59 PM Eastern Time on the date it is due. Late assignments will have 10 points deducted for each 24 hour period or part thereof, past the due date that they are submitted, unless there is a documented personal or family emergency or illness. Assignments that are sent to the instructor(s) via e-mail will not be accepted and the student will receive a 0 for that assignment.
3) Following Directions: In order to receive full credit for each assignment, they must be turned in on time and all sections completed. Detailed instructions for completion of these exercises will be provided on Blackboard.
Failure to follow directions for the assignment (excessive spelling or grammatical errors, etc.) may result in the loss of 5 points from the final grade for each occurrence.
4) Course grading depends heavily on the student's ability to convey his or her thoughts in writing. Papers that are poorly written and/or have errors in spelling or grammar will not effectively convey the student's ideas. Thus students who have difficulty with writing should seek help from a writing specialist and/or private tutor.
- Assignments, Exams and Tests: Date Topic
Week 1 Introduction & Overview
Applied Modeling I
Week 2 Applied Modeling II
Week 3 Applied Modeling III
Week 4 Approaches for Multiple Comparisons
Modeling Assignment I Due
Week 5 Analytic Approaches to Bias
Week 6 Sensitivity Analyses & External Adjustment
Modeling Assignment II Due
Week 7 Multiple Bias Analyses I
Week 8 Multiple Bias Analyses II
Week 9 MID TERM EXAM
Week 10 Statistical Methods for Analyses with Missing Data I
Assessing Bias Assignment Due
Week 11 Statistical Methods for Analyses with Missing Data II
Week 12 Statistical Methods for Analyses with Missing Data III
Week 13 Meta-Analyses I
Missing Data Assignment Due
Week 14 Meta Analyses II
Week 15 Meta-Analyses III
Meta-Analysis Assignment Due
Week 16 FINAL EXAM
- Attendance Policy: Course Attendance at First Class Meeting Policy for Graduate Students: For structured courses, 6000 and above, the College/Campus Dean will set the first-day class attendance requirement. Check with the College for specific information. This policy is not applicable to courses in the following categories: Educational Outreach, Open University (TV), FEEDS Program, Community Experiential Learning (CEL), Cooperative Education Training, and courses that do not have regularly scheduled meeting days/times (such as, directed reading/research or study, individual research, thesis, dissertation, internship, practica, etc.). Students are responsible for dropping undesired courses in these categories by the 5th day of classes to avoid fee liability and academic penalty. (See USF Regulation Registration - 4.0101,
http://usfweb2.usf.edu/usfgc/ogc%20web/currentreg.htm)
Attendance Policy for the Observance of Religious Days by Students: In accordance with Sections 1006.53 and 1001.74(10)(g) Florida Statutes and Board of Governors Regulation 6C-6.0115, the University of South Florida (University/USF) has established the following policy regarding religious observances: (http://usfweb2.usf.edu/usfgc/gc_pp/acadaf/gc10-045.htm)
In the event of an emergency, it may be necessary for USF to suspend normal operations. During this time, USF may opt to continue delivery of instruction through methods that include but are not limited to: Blackboard, Elluminate, Skype, and email messaging and/or an alternate schedule. Its the responsibility of the student to monitor Blackboard site for each class for course specific communication, and the main USF, College, and department websites, emails, and MoBull messages for important general information.
- Policy on Make-up Work: Students who are ill should not attend class.
Students with a documented personal or family illness (surgery, hospitalization, etc.) or personal or family emergency (e.g., death, car accident, etc) will be permitted to make-up missed assignments. Students should contact the course instructor as soon possible to make arrangements. Students will not be permitted to make-up the missed assignment(s) until proper documentation is provided. Students without proper documentation will not be permitted to make-up missed assignments. Students should consult the USF policy on Academic Integrity for additional information.
- Program This Course Supports: PhD in Public Health with a concetration in Epidemiology
- Course Concurrence Information: Doctoral programs offered in other departments in the College of Public Health: Community and Family Health, Global Heath, Environmental and Occupational Health, & Health Policy & Management.
- if you have questions about any of these fields, please contact chinescobb@grad.usf.edu or joe@grad.usf.edu.