Graduate Course Proposal Form Submission Detail - PHC7703
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Approved by SCNS
Submission Type: Change
Course Change Information (for course changes only): We are requesting the change in title to fit into our Epidemiology Methods sequence. We already have methods courses 1 -3 and this will fit into the sequence as the 4th course.
Comments: for PhD in PH - Epi Conc. Previously approved, but missing SCNS required fields. Resubmitted. Reapproved 5/5/14. SCNS approved eff 11/1/14
- Department and Contact Information
Tracking Number Date & Time Submitted 4942 2014-02-13 Department College Budget Account Number Epidemiology and Biostatistics PH Contact Person Phone Wendy Nembhard 8139746861 email@example.com
- Course Information
Prefix Number Full Title PHC 7703 Advanced Research Methods in Epidemiology Is the course title variable? N Is a permit required for registration? N Are the credit hours variable? N Is this course repeatable? If repeatable, how many times? Credit Hours Section Type Grading Option 3 C - Class Lecture (Primarily) R - Regular Abbreviated Title (30 characters maximum) Advanced Reesarch Methods Course Online? Percentage Online C - Face-to-face (0% online) 0
PHC 6010, PHC 6011, PHC 6016, PHC 6053, PHC 6051
This course uses a combination of classic methodologic papers and data analysis examples to create expertise in calculating and judging an unbiased measure of association. It also provides a foundation for students to further develop skills in epi methods
A. Please briefly explain why it is necessary and/or desirable to add this course.
Needed to compete with national trends
B. 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?
C. Has this course been offered as Selected Topics/Experimental Topics course? If yes, how many times?
Yes, 2 times
D. What qualifications for training and/or experience are necessary to teach this course? (List minimum qualifications for the instructor.)
PhD in Epidemiology
Significant experience in data analysis using SAS
- Other Course Information
Objectives are split into understanding concepts and gaining expertise in using methodological tools.
Conceptual: Students should gain:
1. expertise at judging causality between an exposure and an outcome
2. an in-depth understanding of the impact of an exposure on disease incidence (attributable risk)
3. an in-depth understanding of confounding.
4. an in-depth understanding of effect modification/interaction
5. an in-depth understanding of selection bias
6. an in-depth understanding of misclassification
7. an in-depth understanding of matching and when it is appropriate to match
Methodological: Students should learn:
8. Non-modeling methods to adjust an association for confounding
9. Modeling methods to adjust an association for confounding including logistic regression, proportional hazards regression and piecewise exponential log-linear models
10. Methods for measuring validity and reliability including interclass correlation coefficients, extended kappas and receiver operating curves
11. Methods for proper assessment of synergism, including evaluating the relative excess risk due to interaction
12. Methods for proper analysis of matched studies
13. To learn to critically read methodologic development papers with a long term of being positioned to write such paper
B. Learning Outcomes
1. Critically evaluate and use scientific theories and frameworks relevant to public health.
2. Synthesize knowledge from a broad range of disciplines in public health.
3. Demonstrate mastery of methods of data collection and analysis.
4. Critically analyze research literature.
C. Major Topics
Lecture 1: Causal Inference - (When Genius Errs - The RA Fisher Controversy);
Lab Assignment 1: Randomization and Confounding and statistics from
Lecture 2: Review of direct adjustment/Statistics based on expectation - Part I: SMR's and PMR's
Discussion 1: Beta-Blockers and Anti-depressants Assignment 1 Due
Lab: Assignment 2 (Direct and indirect adjustment)
Discussion 2 assigned: Standardized and proportional mortality ratios
Lecture 3: Statistics based on expectation- Part II: Attributable Risk.;
Discussion 2: Standardized and proportional mortality ratios.;
Assignment 2 due;
Discussion 3 assigned: Understanding attributable risk
Lab: Assignment 3 Measures of strength and impact
Lecture 4: Confounding and stratified analysis;
Discussion 3: Understanding attributable risk;
Assignment 3 due;
Lab: Assignment 4: Assessment of confounding using a stratified analysis;
Discussion 4 assigned: Confounding by indication: the Fenoterol battle
Lecture 5: Effect Modification;
Discussion 4 Confounding by indication: The Fenoterol battle;
Assignment 4 due;
Lab: Assignment 5: Assessment of effect modification using stratified analysis;
Discussion 5 assigned: Differential use of antihypertensives by race.
Lecture 6: Logistic Regression
Discussion 5: Differential use of antihypertensives by race.;
Assignment 5 due;
Lab: Assignment 6 (Logistic regression-assessing confounding and effect modification).:
Research assignment in lieu of discussion assigned: RERI and the assessment of synergism.
Lecture 7: Logistic Regression Continued;
Lab: Assignment 6 Continued;
Lecture 8: Selection Bias;
Discussion 6 assigned: Coffee and Pancreatic Cancer; Assignment 6 Due; Research assignment on RERI due.
Lecture 9: Person years and Life-tables;
Discussion 6: Coffee and Pancreatic Cancer;
Discussion 7 assigned: Survival following kidney transplant; Lab: Assignment 7: LIFETEST
Lecture 10: Proportional hazards regression;
Discussion 7: Survival following kidney transplant..
Assignment 7 Due;
Lab: Assignment 8: PHREG;
Lecture 11: The Analysis and Interpretation of Matched Studies;
Assignment 8 Due;
Exercise: Gain or loss in efficiency with matched designs; Lab: Assignment 9: Analysis of matched studies;
Discussion 8 assigned: Gain or loss in efficiency with matched studies.
Lecture 12: Sensitivity, Specificity and Misclassification bias; Discussion 8: Gain or loss in efficiency with matched studies;
Discussion 9 assigned: Adjusting for misclassification of hypercholesterolemia.
Lecture 13: Assessing validity: agreement statistics, kappas, interclass correlation coefficients and receiver operator curves; Discussion 9: Adjusting for misclassification of Hypercholesterolemia;
Lab assignment 10: Using Logistic regression for ROC curves; Discussion 10 assigned: Assessing validity/ROC curves.
Lecture 14: Comparison of 4 modeling procedures for calculating survival ratios.;
Assignment 10 due;
Discussion 10 : Assessing validity/ROC curves; Lab Assignment 11: Comparison of 4 modeling techniques for calculating survival ratios.
Assignment 11 due, review for Final
1) Allison: Survival Analysis Using the SAS System A Practical Guide.
2) SAS: Logistic Regression Examples using the SAS System
3) Rothman, Greenland and Lash. Modern Epidemiology 3rd edition
E. Course Readings, Online Resources, and Other Purchases
Course readings as provided
F. Student Expectations/Requirements and Grading Policy
G. Assignments, Exams and Tests
Homework has 2 parts: a data analysis assignment and a discussion.
1. 11 Homework (Data, except final) 44% (4 points each)
2. 10 Homework (Discussion) 20% (2 points each)
3. Research on RERI assignment 6%
4. 2 Exams 30% (15 points each)
H. Attendance Policy
Course Attendance at First Class Meeting Ė 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 Ė Registration - 4.0101,
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. Itís 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.
I. Policy on Make-up Work
Students must contact the instructor regarding make-up work due to illness or emergency. Students should consult the USF Policy on Academic Integrity for more information.
Plagiarism will not be tolerated and is grounds for failure. Review USF Academic Dishonesty and Disruption of Academic Process Policy at:
The University of South Florida has an account with an automated plagiarism detection service (SafeAssign), which allows instructors and students to submit student assignments to be checked for plagiarism. I (the instructor) reserve the right to 1) request that assignments be submitted as electronic files and 2) submit studentsí assignments to SafeAssign, or 3) request students to submit their assignments to SafeAssign through myUSF. Assignments are compared automatically with a database of journal articles, web articles, the internet and previously submitted papers. The instructor receives a report showing exactly how a studentís paper was plagiarized.
NOTE: An institution may not release a paper to a plagiarism detection software without the studentís prior consent unless all personally identifiable information has been removed, such as a studentís name, social security number, student number, etc.. Note that a paper/essay is considered an educational record and an institution may not ask a student to waive their rights under FERPA for the purpose of submitting papers to a plagiarism detection software.
For more information about Plagiarism and SafeAssign, visit:
Plagiarism tutorial: http://www.cte.usf.edu/plagiarism/plag.html
Additional: Copying a substantial amount of a homework or exam from another student in the class will carry the same penalties as plagiarism, and may result in a F for the class.
J. Program This Course Supports
PhD in Public Health with Concentration in Epidemiology
- Course Concurrence Information
Other concentrations within the PhD in Public Health