Syllabus
Graduate Programs in Public Health
GPH 718: Biostatistics II – Fall B 2024
Credits - 3
Description
This course builds on GPH 716 (Biostatistics). Familiarity with the basic principles of data collection, one-and-two-sample confidence intervals, and hypothesis testing, as well as one-way ANOVA and the fundamentals of simple linear regression, is assumed. The course takes a more in-depth look at simple linear regression extending to multiple linear regression. Additionally, it will cover topics in probability, diagnostic and screening tests, categorical data analysis, non-parametrics, and logistic regression.
Pre-Requisites
GPH 716 Biostatistics
GPH 719 Research Methods
Materials
Learning Objectives and Outcomes
Course Outcomes
- Perform estimation and prediction using simple linear regression.
- Perform logistic regression on binary outcomes.
- Describe and solve probability using discrete probability rules, with an emphasis on probability calculations for screening tests.
- Describe nonparametric testing alternatives to classical hypothesis tests for the mean
- Perform analyses of contingency tables, including estimating measures of association.
- Describe the role of several predictors in a multiple regression model
Program Competencies
PC 2: Evaluate the appropriateness of study designs relative to the needs of priority populations
PC 5: Demonstrate the ability to integrate key components of disease surveillance and screening into public health practice
PC 18: Source credible public health information to inform practice
PC 19: Execute public health research, evaluation, policy, and/or practice using informed data analysis and interpretation
CEPH Foundational Competencies
FC 3: Analyze quantitative and qualitative data using biostatistics, informatics, computer-based programming and software, as appropriate
FC 4: Interpret results of data analysis for public health research, policy or practice
Assignments
Forum Discussions
Discussion forums are an essential part of the online course experience. Discussion prompts build on readings, lectures, and course content, allowing students to contribute to the learning experience by collaborating with the instructor and peers. Read the prompts carefully and use the rubrics to confirm how discussions will be graded.
Unless otherwise specified in the course, initial discussion posts are due by Sunday at 11:59 PM ET and any response posts are due by Wednesday at 11:59 PM ET.
Weekly Assignments
Each weekly module features one assignment, set up as an untimed quiz with written-response answer fields. These activities require you to complete statistical problem sets, and beginning in Module 3, will require the use of the SAS software (see Module 1 for an Intro to SAS).
Grading Policy
Your grade in this course will be determined by the following criteria:
Grade Breakdown
| Assignment/Task | Point value |
|---|---|
| Module 1 Acknowledgement of Academic Engagement Quiz | 1 |
| Discussions | 5 x 5 = 25 points |
| Module 1 Probability Assignment | 8 points |
| Module 2 Screening Tests Assignment | 9 points |
| Module 3 Nonparametrics Assignment | 9 points |
| Module 4 Contingency Table Assignment | 9 points |
| Module 5 Linear Regression Assignment | 9 points |
| Module 6 Multiple Linear Regression Assignment | 9 points |
| Module 7 Logistic Regression Assignment | 9 points |
| Module 8 Final Exam | 12 points |
| Total | 100 points |
Grade Scale
| Grade | Points Grade | Point Average (GPA) |
| A | 94 – 100% | 4.00 |
| A- | 90 – 93% | 3.75 |
| B+ | 87 – 89% | 3.50 |
| B | 84 – 86% | 3.00 |
| B- | 80 – 83% | 2.75 |
| C+ | 77 – 79% | 2.50 |
| C | 74 – 76% | 2.00 |
| C- | 70 – 73% | 1.75 |
| D | 64 – 69% | 1.00 |
| F | 00 – 63% | 0.00 |
Schedule
Course Calendar
Week 1: Oct 30 – Nov 6
Week 2: Nov 6 – Nov 13
Week 3: Nov 13 – Nov 20
Week 4: Nov 20 – Nov 27
Week 5: Nov 27 – Dec 4
Week 6: Dec 4 – Dec 11
Week 7: Dec 11 – Dec 18
Week 8: Dec 18 – Dec 22
The assignment and discussion descriptions mentioned below are summaries. Please make sure to review the full prompts in Brightspace.
Week 1: Introduction to Probability
Learning Outcomes
- Understand the three axioms of probability
- Apply probability rules to solve probability problems
Learning Activities
- Probability Assignment
- Discussion
- Welcome to GPH-718. Begin by introducing yourself to the class. What is your background in Biostatistics? what are you most excited about? In what ways will this course come in handy for your Public Health Career?
- Discussion
- A famous problem in probability comes from the game show “Let’s Make a Deal.” In it, a contestant is shown three doors. Behind one door is a new car, and behind the other doors, there is nothing. The contestant is asked to pick one of the three doors. The host then opens up one of the two that was not chosen which always reveals that there is nothing behind that opened door. The contestant is then asked if they would like to change their chosen door to the other unopened one.
-
Acknowledgement of Academic Engagement Quiz
Week 2: Properties of Screening and Diagnostics
Learning Outcomes
- Apply concepts of sensitivity and specificity to evaluate diagnostic and screening tests
- Understand the relationships among positive/negative predictive values, sensitivity/specificity, and false positive/negative
Learning Activities
- Screening/Diagnostic Test Assignment
- Discussion
- In the article, RPR tests for syphilis have a sensitivity of 86% and a specificity of approximately 92%. Given a syphilis prevalence rate of 5 cases per 100,000 people, can you calculate the predictive value positive and predictive value negative? What does this suggest about the usefulness of screening the general population?
Week 3: Nonparametrics
Learning Outcomes
- Perform nonparametric equivalents to one- and two-sample parametric tests
- Analyze the assumptions and limitations of nonparametric tests
Learning Activities
- Nonparametrics Assignment
- Discussion
- In the second paragraph of page 117 in the NEJM article, it says that the Wilcoxon rank sum test was used to determine that the aortic lesion in those with bone marrow from knockout mice was twice as large as the lesions in those not receiving such bone marrow. Why do you think the Wilcoxon rank sum test was used? What is the “standard” parametric alternative to this test? Are there reasons given in the article as to why a nonparametric test was used? Do you believe the conclusion reached in this case? Why or why not?
Week 4: Contingency Table Analysis
Learning Outcomes
- Create and analyze contingency tables for independent data
- Apply exact methods for sparse contingency tables for independent data
- Create and analyze contingency tables for paired data
Learning Activities
- Contingency Table Assignment
Week 5: Inference for Simple Linear Regression
Learning Outcomes
- Evaluate simple linear regression models
- Synthesize inferences and predictions in a simple linear regression model setting
Learning Activities
- Linear Regression Assignment
Week 6: Multiple Regression
Learning Outcomes
- Incorporate more than one predictor in a linear regression model
Learning Activities
- Multiple Regression Assignment
- Discussion
- The second paragraph of the Statistical Analysis section of the NEJM states: “The prespecified plan was to use linear regression, adjusted for prestroke score on the utility-weighted modified Rankin scale, site, and covariates associated with scores on the modified Rankin scale (baseline NIHSS score, age, and previous transient ischemic attack [TIA] or stroke).” Based on this information, write out the intended regression model listing all the independent variables. The authors state that the model was not used because assumptions were not satisfied. Does this give you enough information to know if the model they ended up utilizing was appropriate? Justify your reasoning.
Week 7: Logistic Regression
Learning Outcomes
- Model binary outcomes in a logistic regression
Learning Activities
- Logistic Regression Assignment
- Discussion:
- Refer to Table 1 in the NEJM letter. Why do the estimates for the odds ratios and confidence intervals differ? Do you agree with the authors doing both sets of analyses?
In response to 1 peer, state whether you agree with the authors’ analyses or not. Describe the potential issue with doing multiple analyses using the same variables on the same dataset.
- Refer to Table 1 in the NEJM letter. Why do the estimates for the odds ratios and confidence intervals differ? Do you agree with the authors doing both sets of analyses?
Week 8: Topics in Logistic Regression
Learning Outcomes
- Incorporate more than one predictor in a logistic regression model
- Evaluate confounding and interaction in logistic regression
Learning Activities
- Final Exam
Student Resources
Online Student Support
Your Student Support Specialist is a resource for you. Please don't hesitate to contact them for assistance, including, but not limited to course planning, current problems or issues in a course, technology concerns, or personal emergencies.
Questions? Visit the Student Support Public Health page
UNE Libraries:
- Library Access for all students: Your library login ID and password are the same as the ones you use to log into Brightspace.
- Public Health Databases: https://library.une.edu/library-materials/find/research-by-subject/public-health/
- Library Questions: Ask a librarian or phone library staff at (207) 602-2361 or (207) 221-4330.
UNE Student Academic Success Center
UNE's Student Academic Success Center (SASC) offers a range of free online services to support your academic achievement. Writing support, ESOL support, study strategy and learning style consultations, as well as downloadable resources, are available to all matriculating students. The SASC also offers tutoring for GPH 712 Epidemiology, GPH 716 Biostatistics, GPH 717 Applied Epidemiology, GPH 718 Biostatistics II, and GPH 719 Research Methods. To make an appointment for any of these services, go to une.tutortrac.com. For more information and to view and download writing and studying resources, please visit:
Information Technology Services (ITS)
- ITS Contact: Toll Free Help Desk 24 hours/7 days per week at 1-877-518-4673
Accommodations
Any student who would like to request, or ask any questions regarding, academic adjustments or accommodations must contact the Student Access Center at (207) 221-4438 or pcstudentaccess@une.edu. Student Access Center staff will evaluate the student's documentation and determine eligibility of accommodation(s) through the Student Access Center registration procedure.
Online Peer Support
Togetherall is a 24/7 communication and emotional support platform monitored by trained clinicians. It’s a safe place online to get things off your chest, have conversations, express yourself creatively, and learn how to manage your mental health. If sharing isn’t your thing, Togetherall has other tools and courses to help you look after yourself with plenty of resources to explore. Whether you’re struggling to cope, feeling low, or just need a place to talk, Togetherall can help you explore your feelings in a safe supportive environment. You can join Togetherall using your UNE email address.
Information Technology Services (ITS)
Students should notify their Student Support Specialist and instructor in the event of a problem relating to a course. This notification should occur promptly and proactively to support timely resolution.
ITS Contact: Toll-Free Help Desk 24 hours/7 days per week at 1-877-518-4673.
Career Ready Program
The College of Professional Studies supports its online students and alumni in their career journey!
The Career Ready Program provides tools and resources to help students explore and hone in on their career goals, search for jobs, create and improve professional documents, build professional network, learn interview skills, grow as a professional, and more. Come back often, at any time, as you move through your journey from career readiness as a student to career growth, satisfaction, and success as alumni.
Policies
AMA Writing Style Statement
The American Medical Association Manual (AMA) of Style, 11th edition is the required writing format for this course. Additional support for academic writing and AMA format is provided throughout the coursework as well as at the UNE Portal for Online Students.
Online resources: AMA Style Guide
Turnitin Originality Check and Plagiarism Detection Tool
The College of Professional Studies uses Turnitin to help deter plagiarism and to foster the proper attribution of sources. Turnitin provides comparative reports for submitted assignments that reflect similarities in other written works. This can include, but is not limited to, previously submitted assignments, internet articles, research journals, and academic databases.
Make sure to cite your sources appropriately as well as use your own words in synthesizing information from published literature. Webinars and workshops, included early in your coursework, will help guide best practices in APA citation and academic writing.
You can learn more about Turnitin in the guide on how to navigate your Similarity Report.
Technology Requirements
Please review the technical requirements for UNE Online Graduate Programs: Technical Requirements
Course Evaluation Policy
Course surveys are one of the most important tools that University of New England uses for evaluating the quality of your education, and for providing meaningful feedback to instructors on their teaching. In order to assure that the feedback is both comprehensive and precise, we need to receive it from each student for each course. Evaluation access is distributed via UNE email at the beginning of the last week of the course.
Late Policy
Students are responsible for submitting work by the date indicated in Brightspace.
Quizzes and Tests: Quizzes and tests must be completed by the due date. They will not be accepted after the due date.
Assignments: Unless otherwise specified, assignments will be accepted up to 3 days late; however, there is a 10% grade reduction (from the total points) for the late submission. After three days the assignment will not be accepted.
Discussion posts: If the initial post is submitted late, but still within the discussion board week, there will be a 10% grade reduction from the total discussion grade (e.g., a 3 point discussion will be reduced by 0.3 points). Any posts submitted after the end of the Discussion Board week will not be graded.
Please make every effort ahead of time to contact your instructor and your student support specialist if you are not able to meet an assignment deadline. Arrangements for extenuating circumstances may be considered by faculty.
Student Handbook Online - Policies and Procedures
The policies contained within this document apply to all students in the College of Graduate and Professional Studies. It is each student's responsibility to know the contents of this handbook.
UNE Course Withdrawal
Please contact your student support specialist if you are considering dropping or withdrawing from a course. The last day to drop for 100% tuition refund is the 2nd day of the course. Financial Aid charges may still apply. Students using Financial Aid should contact the Financial Aid Office prior to withdrawing from a course.
Academic Integrity
The University of New England values academic integrity in all aspects of the educational experience. Academic dishonesty in any form undermines this standard and devalues the original contributions of others. It is the responsibility of all members of the University community to actively uphold the integrity of the academy; failure to act, for any reason, is not acceptable. For information about plagiarism and academic misconduct, please visit https://www.une.edu/studentlife/plagiarism.
Academic dishonesty includes, but is not limited to the following:
- Cheating, copying, or the offering or receiving of unauthorized assistance or information.
- Fabrication or falsification of data, results, or sources for papers or reports.
- Action which destroys or alters the work of another student.
- Multiple submissions of the same paper or report for assignments in more than one course without permission of each instructor.
- Plagiarism, the appropriation of records, research, materials, ideas, or the language of other persons or writers and the submission of them as one's own.
Charges of academic dishonesty will be reviewed by the Program Director. Penalties for students found responsible for violations may depend upon the seriousness and circumstances of the violation, the degree of premeditation involved, and/or the student’s previous record of violations. Appeal of a decision may be made to the Dean whose decision will be final. Student appeals will take place through the grievance process outlined in the student handbook.