Syllabus

Graduate Programs in Public Health

GPH 718 – Advanced Biostatistics – Spring B 2018

Credits - 3

Description

This course is a continuation of GPH 716 (Biostatistics). The course will assume 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. It will focus on 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, nonparametics, and logistic regression. 

Materials

  • Pagano M, Gauvreau K. Principles of Biostatistics. 2nd ed. Pacific Grove, CA: Duxbury; 2007.
  • Stata Data Analysis and Statistical Software, Stata/IC (https://www.stata.com/order/new/edu/gradplans/student-pricing/) Must be purchased and downloaded before the third week of class.

    Steps to purchase:

    • Choose your country
    • Click on Educational
    • You will need at least a 6 month license of Stata/IC

Learning Objectives and Outcomes

 

Program Outcomes Course Outcomes Weekly Outcomes
Analyze quantitative and qualitative data using biostatistics, informatics, computer-based programming and software, as appropriate
Performing estimation and prediction using simple linear regression. Week 5 – Evaluate simple linear regression models

Week 5 – Synthesize inferences and predictions in a simple linear regression model setting

Perform logistic regression on binary outcomes.

Week 7 – Model binary outcomes in a logistic regression

Week 8 – Incorporate more than one predictor in a logistic regression model

Week 8 – Evaluate confounding and interaction in logistic regression

Interpret results of data analysis for public health research, policy or practice
Describe and solve probability using discrete probability rules, with an emphasis on probability calculations for screening tests. Week 1 – Understand the three axioms of probability

Week 1 – Apply probability rules to solve probability problems

Week 2 – Apply concepts of sensitivity and specificity to evaluate diagnostic and screening tests

Week 2 – Understand the relationships among positive/negative predictive values, sensitivity/specificity, and false positive/negative

Describe nonparametric testing alternatives to classical hypothesis tests for the mean Week 3 – Perform nonparametric equivalents to one- and two-sample parametric tests

Week 3 – Analyze the assumptions and limitations to nonparametric tests

Perform analyses of contingency tables, including estimating measures of association. Week 4 – Create and analyze contingency tables

Week 4 – Apply exact methods for sparse contingency tables

Describe the role of several predictors in a multiple regression model. Week 6 – Incorporate more than one predictor in a linear regression model

 

Assignments

Forum Discussions

Each student is expected to post at least twice each week in response to forum questions on that week’s topic. Because this is an online course, the online discussion portion is an important way to exchange ideas with your classmates. Students will be graded on their participation and effort of their posts. These posts will take time to complete but they are an essential part of this on-line course and a great way to get to know your colleagues. Please be familiar with the course material (readings/lectures) before posting each week. Full marks will be given to those who ask questions, bring in new data from the literature or other resources, and demonstrate a thorough understanding of the topics for the week.

Worksheets

Each week, you will download, complete, and submit a worksheet that has you applying what you learned in that module. These are always due at the end of their respective weeks. The Final Exam is also a worksheet. 

Grading Policy

Your grade in this course will be determined by the following criteria:

Grade Breakdown

Assignment / TaskGrade Point Value
Discussions5 x 5 = 25 points
Probability Worksheet9 points
Screening / Diagnostic Worksheet9 points
Nonparametric Problem Worksheet9 points
Contingency Table Analysis Worksheet9 points
Regression Analysis Worksheet Part 19 points
Regression Analysis Worksheet Part 29 points
Logistic Regression Analysis Worksheet9 points
Final Exam12 points
Total100 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: Feb 28 – Mar 7
Week 2: Mar 7 – Mar 14
Week 3: Mar 14 – Mar 21
Week 4: Mar 21 – Mar 28
Week 5: Mar 28 – Apr 4
Week 6: Apr 4 – Apr 11
Week 7: Apr 11 – Apr 18
Week 8: Apr 18 – Apr 22 (Sunday)

 

Week 1: Introduction to Probability

Learning Outcomes

  • Understand the three axioms of probability
  • Apply probability rules to solve probability problems

Readings/Videos

  • Read: Pagano and Gauvreau: Chapter 6.1 through 6.3; pages 125-135
  • Review: Pagano and Gauvreau:  Chapters 9, 10, and 11 as needed to re-familiarize with confidence intervals and hypothesis tests.
  • Watch: Lecture

Assignments/Tasks

  • Probability worksheet
  • 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 he or she would like to change their chosen door to the other unopened one.  Should he/she?  Explain why or why not.

Week 2: Properties of Screening and Diagnostic Tests

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

Readings/Videos

  • Read: Pagano and Gauvreau: Chapter 6.4 and 6.5; pages 135-149
  • Read:  “Screening for Syphilis Infection in Nonpregnant Adults and Adolescents, Clinical Review & Education
  • Watch: Lecture

Assignments/Tasks

  • Screening/diagnostic test worksheet
  • Discussion: The article states that 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? 

Week 3: Nonparametrics

Learning Outcomes

  • Perform nonparametric equivalents to one- and two-sample parametric tests
  • Analyze the assumptions and limitations of nonparametric tests

Readings/Videos

  • Read: Pagano and Gauvreau: Chapter 13; pages 302-316
  • Read: “Clonal Hematopoiesis and Risk of Atherosclerotic Cardiovascular Disease,” New England Journal of Medicine.
  • Watch: Lecture and Stata Tutorial

Assignments/Tasks

  • Nonparametric problem set
  • 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.  

Week 4: Analyses of Contingency Tables

Learning Outcomes

  • Create and analyze contingency tables
  • Apply exact methods for sparse contingency tables

Readings/Videos

  • Read: Pagano and Gauvreau: Chapter 15; pages 342-357
  • Read: Pagano and Gauvreau: Chapter 16; pages 374-383
  • Watch: Lecture and Stata Tutorial

Assignments/Tasks

  • Contingency table analysis

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

Readings/Videos

  • Read: Pagano and Gauvreau: Chapter 18; pages 415-453
  • Watch: Lecture

Assignments/Tasks

  • Complete regression analysis activity using a single predictor

Week 6: Multiple Regression

Learning Outcomes

  • Incorporate more than one predictor in a linear regression model

Readings/Videos

  • Read: Pagano and Gauvreau: Chapter 19; pages 449-465
  • Read: “Early versus Later Rhythm Analysis in Patients with Out-of-Hospital Cardiac Arrest,” The New England Journal of Medicine.
  • Watch: Lecture

Assignments/Tasks

  • Complete regression analysis worksheet for situations involving two or more predictors
  • Discussion:  In the last paragraph on page 789 continuing on page 790,, the authors state that they determined the difference in the outcome between patient groups, “adjusted for baseline measurements” through the use of multiple regression.  What do they mean by saying this?  Does this give you enough information to determine whether the analysis was done appropriately?  Explain.

Week 7: Logistic Regression

Learning Outcomes

  • Model binary outcomes in a logistic regression

Readings/Videos

  • Read: Pagano and Gauvreau: Chapter 20; pages 470-484
  • Read: “Association Between Maternal Use of Folic Acid Supplements and Risk of Autism Spectrum Disorders in Children,” Journal of the American Medical Association.
  • Watch: Lecture

Assignments/Tasks

  • Logistic regression analysis worksheet
  • Discussion: Read the Statistical Analysis section on page 572. Can you determine what the logistic regression models the authors ran looked like? Do you agree with the procedure they used? 

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

Readings/Videos

Assignments/Tasks

  • 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:

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.

Student 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:

  1. Cheating, copying, or the offering or receiving of unauthorized assistance or information.
  2. Fabrication or falsification of data, results, or sources for papers or reports.
  3. Action which destroys or alters the work of another student.
  4. Multiple submissions of the same paper or report for assignments in more than one course without permission of each instructor.
  5. 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.

Attendance Policy

8 week: Students taking online graduate courses through the College of Professional Studies will be administratively dropped for non-participation if a graded assignment/discussion post is not submitted before Sunday at 11:59 pm ET of the first week of the term. Reinstatement is at the purview of the Dean's Office.

16 week: Students taking online graduate courses through the College of Professional Studies will be administratively dropped for non-participation if a graded assignment/discussion post is not submitted before Friday at 11:59 pm ET of the second week of the term. Reinstatement is at the purview of the Dean's Office.

Student Handbook Online - Policies and Procedures

The policies contained within this document apply to all students in the College of Professional Studies. It is each student's responsibility to know the contents of this handbook.

UNE Online Student 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 UNE Plagiarism Policies.

Academic dishonesty includes, but is not limited to the following:

  1. Cheating, copying, or the offering or receiving of unauthorized assistance or information.
  2. Fabrication or falsification of data, results, or sources for papers or reports.
  3. Action which destroys or alters the work of another student.
  4. Multiple submissions of the same paper or report for assignments in more than one course without permission of each instructor.
  5. 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.