Skip to content

Course: Modeling Normally Distributed Data with Repeated Measures

Photo of
Hosted By
Juliana C. and EP
Course: Modeling Normally Distributed Data with Repeated Measures

Details

Hey R-Ladies SD members,

This short course is being hosted by OCRUG on Zoom and they have kindly invited us to participate.

There is a nominal cost, but they would like all to attend who want to. So there are a number of free tickets available. Just email john@jppeach.com for details.

The event details provided by OCRUG are as follows:

Registration is on Eventbrite (https://www.eventbrite.com/e/ocrug-modeling-normally-distributed-data-with-repeated-measures-tickets-135236340535).

Abstract
This workshop will give you the practical skills and foundational knowledge to effectively use some powerful regression models used by data scientists. When data are collected on the same subjects repeatedly over time (for example, in clinical trials or cohort studies) or under different conditions (for example, in a designed experiment), the measurements within the same individual are modeled as having correlated values. At the workshop, we will consider several models that can be employed to model a normally distributed response variable. The models that we will consider are: random slope and intercept (mixed-effects) model and generalized estimating equations models with unstructured, autoregressive, compound symmetric (exchangeable), and independent working correlation matrices. All models will be run in R version 4.0.3.

The course will be structured as follows. For each part, we will first discuss the theory, then work through an example. After that, the participants will work in small groups in break-out rooms to do hands-on exercises to help reinforce the material. All the files and Rstudio will be made available to the participants.

We would like to use the RStudio Cloud. If you are not familiar with this technology, the participants use a web browser to access RStudio. The environment will be set up and loaded with the code and data that is needed. This way, participants can focus on building models.

The material covered by the workshop will be taken from my recently published book "Advanced Regression Models with SAS and R Applications", CRC Press, 2018.

About the Instructor
Dr. Olga Korosteleva, is a professor of Statistics at the Department of Mathematics and Statistics at California State University, Long Beach (CSULB). She received her Bachelor's degree in Mathematics in 1996 from Wayne State University in Detroit, and a Ph.D. in Statistics from Purdue University in West Lafayette, Indiana, in 2002. Since then she has been teaching mostly Statistics courses in the Master's program in Applied Statistics at CSULB, and loving it!

Dr. Olga is an undergraduate advisor for students majoring in Mathematics with an option in Statistics. She is also the faculty supervisor for the Statistics Student Association. She is also the immediate past-president of the Southern California Chapter of the American Statistical Association (SCASA). Dr. Olga is the editor-in-chief of SCASA's monthly eNewsletter and the author (co-author) of four statistical books.

Schedule

• 06:30-06:40 Introduction
• 06:40-07:30 Mixed-effects Model for Normal Response
• 07:30-07:50 Mixed-effects Model Exercise
• 07:50-08:00 Mixed-effects Model Solution
• 08:00-08:10 Break
• 08:10-08:30 Generalized Estimating Equations (GEE) Model for Normal Response
• 08:30-08:50 GEE Exercise
• 08:50-09:00 GEE Solution
• 09:00-09:30 Additional Exercise and Solution
• 09:30-09:45 Wrap up

We hope to see you all there!

Your R-Ladies SD organizers

Online event
This event has passed