PhD+ Statistical Analysis in R 5: Linear Mixed Effects Models


This is the fifth (and last) session of the Statistical Analysis in R (2022 Fall pilot) series, developed through collaboration with UVA Health’s Health Sciences Library.

In this final session, learners will improve their understanding of linear mixed effects models, useful when data are clustered or collected longitudinally. Learners will develop intuition about when these models may be useful, differences between linear regression models and these mixed models, and will gain experience visualizing the results and interpreting output from these models.


Marieke Jones, Research Data Specialist, UVA Health Sciences Library


Participants MUST have working knowledge of R and RStudio, preferably with previous experience using tidyverse packages (dplyr and ggplot2). This series’ pre-requisite may be met through any of the following:

  • Attendance at Health Sciences Library’s 4 workshops in R (offered monthly)
  • Participation in at least 3 sessions of PhDPlus Data Literacy in R series (offered Spring semester annually)
  • Participation in Brain Immunology and Glia Center Learn R series (offered Fall annually)
  • Completion of a curricular course using R (within the past 3 years)
  • Independent learning of R and instructor approval

Session Dates

Virtual format | Oct 19, Oct 26, Nov 2, Nov 9, Nov 30 (Wednesdays), 10 am – 12 pm (ET)

Please hold dates on your calendar after registration. 


* Registration closes on Oct 14, and instructors will evaluate prerequisites and make announcements by Oct 17.


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