Statistical Methods Seminar Description
Have you always wanted to learn R for a project and haven’t had the time? Do you keep hearing that R is the future and want to find out what all the fuss is about? Tired of paying expensive license fees for statistical software? If this sounds like you, multivariate statistical modeling in R is for you! We will cover all your favorite methods (and maybe a few new ones too!) like regression, mediation, moderation, multilevel models and SEM. All using (free, open-source) R!
Overview: An introductory 5-day course on using R software for common analytic methods in behavioral and social sciences. Topics covered include, regression, mediation and moderation, multilevel modeling (MLM), factor analysis and structural equation modeling (SEM).
Instructor: Alex Schoemann, Ph.D.
Dr. Alexander M. Schoemann, is an Associate Professor of Psychology at East Carolina University. Alex received his PhD from the University of Kansas in 2011 in Social and Quantitative Psychology under the mentorship of Dr. Kristopher Preacher. He has been a Stats Camp instructor since 2012 (after spending several years as a “counselor”). Alex teaches graduate courses in research design, regression, multivariate statistics, structural equation modeling and multilevel modeling. His research is focused on applying advanced quantitative methods to data from behavior sciences. Specific topics of interest include mediation and moderation, power analyses, missing data estimation, meta-analysis, structural equation models and multilevel models. Alex is also interested in developing user friendly software and R packages for advanced methods including applications for power analysis for mediation models (http://marlab.org/power_mediation/).
- Advanced proficiency in multiple linear regression, including use of categorical independent variables.
- Intermediate fluency with statistical software (e.g. SAS, SPSS, or R) which will aid in the use of R (Note that materials for introducing attendees to R software will be shared in advance and the course will begin with a short introduction to R).
Not required but advantageous:
- At least limited experience (e.g., graduate-level course) with multivariate data analysis.
- At least limited experience using R
No level of proficiency beyond basic awareness is assumed for skills related to:
- Factor Analysis, SEM, or MLM.
- Advanced mathematical or statistical topics such as matrix algebra or likelihood theory.
- Introduction to R software and importing data into R
- Fitting regression models in R
- Testing mediation and moderation models in R
- MLM in R
- Factor analysis and SEM in R
Note: This course will focus primarily on statistical modeling in R. As such, this course will not provide an in-depth coverage R programming or the TidyVerse. See the Summer Stats Camp course, R Programming for Data Science, for training in this topic area.
Course Software and Computer Support
Participants need to bring a laptop computer with Wi-Fi capabilities.
All statistical software used at Stats Camp will be available, free to participants, on our SMORS (statistical modeling on remote servers) system for the duration of camp.
Note, however, that R and RStudio are the software programs that will be demonstrated. Both programs are free and can be downloaded from https://cloud.r-project.org/ and https://www.rstudio.com/products/rstudio/download/, respectively. Additional directions will be shared with enrolled participants.
Downloadable files used for this course will be provided on the first day of class.
Participants will receive an electronic copy of all course materials, including lecture slides, practice datasets, software scripts, relevant supporting documentation, and recommended readings. Participants will also have access to a video recording of the course.