What R We Doing with Our Data: A Community-Academic Approach to Assessing HIV Data using RStudio

Contact Information
Adolph “AJ” Delgado, Ph.D., M.Ed., M.S.
HCAP Postdoctoral Fellow
Email:

Course Start Date
11/4/2024

Workshop Description

This workshop is designed to equip participants with the essential skills and knowledge needed to work with administrative health data using R and leverage ChatGPT for natural language interaction. Students will learn to access, clean, manipulate, analyze health data, create R Markdown reports for publication on Rpubs, and use ChatGPT for data-related discussions and assistance.

Objectives

By the course’s end, students will:

  1. Access and retrieve administrative health data.
  2. Filter and select relevant data variables.
  3. Manipulate data structures efficiently.
  4. Describe data using statistics and visualizations.
  5. Analyze health data through appropriate methods.
  6. Interpret and communicate data-driven insights.

Required Software

For this course, the required software includes:

  • Required for data analysis in R.
  • R Packages: Necessary for data manipulation, visualization, and analysis.
  • Rpubs Account: Needed for publishing reports.
  • ChatGPT Access: For interactive discussions.
  • Data Sources: Access to relevant datasets.

Online Meeting Time

Adolph Delgado is inviting you to a scheduled Zoom meeting.

Topic: R Studio Workshop Meeting Time: Nov 8, 2024 08:30 AM to 10:30AM Central Time (US and Canada) Every week on Fri, until Dec 20, 2024, 7 occurrence(s) Please download and import the following iCalendar (.ics) files to your calendar system. Weekly: https://utsa.zoom.us/meeting/tJ0lfuirrT8pEtFu-cQo5UxwaOL2RM4CcZDy/ics?icsToken=98tyKuChpjIrGdeRsxGCRox5Gor4d-nztilej7d7iVLmMi8GVxvhN81uYIBSRPvT&meetingMasterEventId=n9qvOZACSHKfFmOppDQMPw

Join Zoom Meeting https://utsa.zoom.us/j/99891334385

Meeting ID: 998 9133 4385

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Meeting ID: 998 9133 4385

Find your local number: https://utsa.zoom.us/u/aeBOBryi9J

Please note the following steps when contacting me:

  • Make sure to thoroughly review the syllabus, announcements, and recorded lectures before sending me an email: sometimes the answer is already available to you.

  • When sending me an email, include BOTH the workshop name (i.e., R Workshop) and your full name (e.g., First Last) in the subject line.

  • In all communications, be specific. I will not reply to an email that says, “How do you analyze the data?”. Alternatively, I will reply to an email that says, “I watched the lecture and understand that I need to calculate a linear regression on HIV prevalence by race. But, the model is showing an error. Please see the attached screenshot.”

  • In each email, professional and respectful language is expected.

  • I check my email regularly from Monday to Friday from 8am to 5pm. Within that timeframe, I will generally respond within 24 hours. If you do not hear back from me, send another email in the event that your message went to my Junk email box.

  • On the weekends, I am generally not available by email, but will reply on the subsequent Monday. If you need to contact me, plan ahead.

Schedule

Week 1: Introduction to Health Data Analysis and RStudio

  • Objectives:
    • Provide an overview of the significance of health data analysis in research and practice.
    • Familiarize participants with the RStudio environment.
    • Demonstrate data import techniques.
  • Recorded Lecture: “Getting Started with RStudio”
  • Tasks to Complete:
    • Complete Pre Survey
    • Download RStudio
    • Create a ChatGPT account
    • Create an R Pubs account
  • Online Meeting Time (Optional): 11/8

Week 2: Data Import and Cleaning

  • Objectives:
    • Import various health data formats.
    • Emphasize the importance of data cleaning for accurate analysis.
  • Recorded Lecture: “Importing and Cleaning Data”
  • Tasks to Complete:
    • Homework 1
  • Online Meeting Time (Optional): 11/15

Weeks 3 & 4: Data Manipulation, Filtering, and Debugging

  • Objectives:
    • Enable efficient manipulation of data structures.
    • Teach techniques for filtering and selecting relevant variables.
    • Introduce debugging tools and methods.
  • Recorded Lectures:
    • “Tidyverse: An Introduction”
    • “Tools for Debugging”
  • Tasks to Complete:
    • Homework 2
  • Online Meeting Time (Optional): 11/22

Week 5: Data Presentation with RMarkdown

  • Objectives:
    • Showcase the basics of RMarkdown as a tool for creating reproducible reports.
  • Recorded Lecture: “RMarkdown: An Authoring Framework to Showcase Your Work to the World”
  • Tasks to Complete:
    • Homework 3
  • Online Meeting Time (Optional):12/6

Week 6: Data Description and Summarization

  • Objectives:
    • Describe health data using appropriate descriptive statistics.
  • Recorded Lecture: “Data Description and Summarization”
  • Tasks to Complete:
    • Homework 4
  • Online Meeting Time (Optional): 12/13

To receive a certificate of completion for this course, participants are required to complete at least 75% of the assigned homework. This ensures that learners have engaged with the core material and practiced the essential skills covered throughout the course. Meeting this requirement demonstrates a commitment to understanding and applying health data analysis techniques using RStudio, providing participants with a solid foundation in the subject.