BIOS-501L Lab for Statistical Methods II

Course Instructors

Alex Edwards

Office Hours: Tuesdays 2:30 - 4pm, Tables outside GCR 105

Sara Khan

Office Hours: Tuesdays, 5 pm to 6:30 pm, Zoom (https://zoom.us/j/9795389280)

Please Note: You may visit any instructor for help, even those not in your lab section.

Course Teaching Assistants

Lindsay Schader
2nd Year PhD
Office Hours: Fridays; 9am to 11am in GCR 344 (Biostatistics Library)

Qingchun Jin
2nd Year MSPH
Office Hours: Wednesdays; 4pm to 5pm in GCR 344 (Biostatistics Library)

Bowen Shi
2nd Year MSPH
Office Hours: Thursdays; 2pm to 4pm in GCR 344 (Biostatistics Library)

Please Note: You may visit any TA for help, even those not in your lab section.

Course Meetings

For Paul’s Labs:

  • This course will at the following times
    • Tuesday 4pm - 5:50pm
    • Tuesday 6pm - 7:50pm

For George’s Lab:

  • This course will at the following times
    • Thursday 4pm - 5:50 pm

Grade Scale

Grade Range
A [95 - 100)
A- [90 - 95)
B+ [85 - 90)
B [80 - 85)
B- [75 - 80)
C [65 - 75)
F < 65

Introduction

This course provides an overview of a number of statistical techniques aimed at the analysis of public health data . We will study correllation (not causation), linear modeling, logistic modeling, and survival analysis. We will address relevant methods in the context of public health data. Each student conducts an analysis project that relates to public health analysis using given data.

This course will primarily use the SAS programming language with an emphasis on reproducible research.

Course Objectives

By the end of the course you will be able to perform the following statistical analyses using the SAS system: simple and multiple linear regression,logistic regression, and model selection. The goal is for you to gain hands-on analytical experience by exploring relevant data sets. By the end of this course, you should feel comfortable using SAS for each step in the process of importing, cleaning, manipulating, analyzing, and interpreting data. The lab is designed to complement the material presented in the BIOS 501 lectures and we design the course to match the speed of the lecture material as closely as possible.

MPH/MSPH Foundational Compentencies

  1. Analyze quantitative data using biostatistics, informatics, computer-based programming and software, as appropriate.
  2. Interpret results of data analysis for public health research, policy or practice.

Textbooks

There are no required text for this course.

Assignments and Weights

Assignments Weight
Labs/Homework Assignments (2-4) 10%
Project Milestone One: Replicate Table One 10%
Project Milestone Two: Data Description and EDA (Reporting) 10%
Project Milestone Three: Data Analysis Plan (Wrte-Up) 30%
Project Milestone Four: Data Analysis Update (Write-Up) 5%
Project Milestone Five: Present Final Findings 35%
Total: 100%

Course Schedule

Module Activity Dates Due
Introduction The 30k Foot View of Modeling 1/20
Correlation Correlation 1/27
Open Lab 2/3
Simple Linear Regression Simple Linear Regression 2/10 Milestone One
Open Lab 2/17
No Lab 2/24 Milestone Two
Multiple Linear Regression Multiple Linear Regression 3/2
Spring Break 3/9
Open Lab 3/16 Milestone Three
Logistic Regression Logistic Regression 3/23
Open Lab 3/30 Milestone Four
Survival Analysis Survival Analysis 4/6
Open Lab 4/13
Open Lab(Room Scheduled No Help) 4/20 Milestone Five

RSPH POLICIES

Accessibility and Accommodations

Accessibility Services works with students who have disabilities to provide reasonable accommodations. In order to receive consideration for reasonable accommodations, you must contact the Office of Accessibility Services (OAS). It is the responsibility of the student to register with OAS. Please note that accommodations are not retroactive and that disability accommodations are not provided until an accommodation letter has been processed.

Students who registered with OAS and have a letter outlining their academic accommodations are strongly encouraged to coordinate a meeting time with me to discuss a protocol to implement the accommodations as needed throughout the semester. This meeting should occur as early in the semester as possible.

Contact Accessibility Services for more information at (404) 727-9877 or . Additional information is available at the OAS website at http://equityandinclusion.emory.edu/access/students/index.html

Honor Code

You are bound by Emory University’s Student Honor and Conduct Code. RSPH requires that all material submitted by a student fulfilling his or her academic course of study must be the original work of the student. Violations of academic honor include any action by a student indicating dishonesty or a lack of integrity in academic ethics. Academic dishonesty refers to cheating, plagiarizing, assisting other students without authorization, lying, tampering, or stealing in performing any academic work, and will not be tolerated under any circumstances.

The RSPH Honor Code states: “Plagiarism is the act of presenting as one’s own work the expression, words, or ideas of another person whether published or unpublished (including the work of another student). A writer’s work should be regarded as his/her own property.” (http://www.sph.emory.edu/cms/current_students/enrollment_services/honor_code.html)

2020-01-28