Below you will find the following:

• The Seminar's Zoom Recording 

• Seminar Description and Speaker's Bio. 

• Handouts 

Seminar Description: 

The defining feature of longitudinal data is that repeated measurements are taken on a subject over time. Models for longitudinal data can study changes over time as well as detect differences at specific time points. Learn the basics of how to fit mixed models to longitudinal data with continuous or discrete outcomes. Examples will introduce theoretical concepts of mixed models and describe the importance of choosing the correct covariance structure to model the within-subject correlation in longitudinal data.

Speaker's Bio: 

Jacqueline Johnson, A Principal Analytical Training Consultant in Global Academic Programs at SAS.

In her role at SAS, she conducts SAS software training at academic campuses around the country and works with faculty to support efforts to develop the future analytics workforce. She holds a DrPH in Biostatistics from UNC Chapel Hill. Prior to SAS, Dr. Johnson’s career focused on statistical analyses of clinical trial data and includes working as a biostatistics faculty in at the UNC Chapel Hill School of Medicine and a biostatistician in the industry at Novartis Pharmaceuticals and Rho, Inc. She has been teaching with SAS in commercial and academic settings since 2009 and joined the SAS Global Academic Programs instructional team full-time in 2019.  Contact: jacqueline.johnson@sas.com

Handouts of this seminar:

• The presentation is available at this link.

• "LEARNING SAS® HAS NEVER BEEN EASIER" is available from this link.