We have recorded and posted brief, free video tutorials on our YouTube Channel, covering a variety of topics in data analysis and hypothesis testing. There are three play lists focused on linear regression, structural equation modeling, and growth modeling. There are also individual videos on topics including the difference between mixture modeling and cluster analysis, how many clusters are needed to fit a multilevel model, introduction to latent class and latent profile analysis, among others.
In the Spring of 2023, we also got bored and experimented with livecasting methods discussions in a series called CenterStat Unscripted. In between throwing coffee creamers and whiteboard markers at one another, we attempted to shed insight on topics like Type I & II Errors and statistical power, moving from multiple regression to structural equation modeling, and multilevel models for intensive longitudinal data. Maybe we’ll record another season some day and maybe not, but for now the play list consists of 13 videos.
New videos are added as time allows and you can subscribe to our channel or follow us on social media to be alerted to new content. Please also feel free to contact us and suggest topics that you might find beneficial.
Self-Paced Workshops
Free Introduction to Structural Equation Modeling
Instructors: Dan Bauer & Patrick Curran
16 hours
Latent Curve Modeling
Instructors: Dan Bauer & Patrick Curran
12 hours
Longitudinal Structural Equation Modeling
Instructors: Dan Bauer & Patrick Curran
20 hours
Multilevel Models for Longitudinal Data
Instructors: Dan Bauer & Patrick Curran
16 hours
Multilevel Models for Hierarchical Data
Instructors: Dan Bauer & Patrick Curran
12 hours
Modern Missing Data Analysis
Instructor: Craig Enders
12 hours
Mixture Modeling and Latent Class Analysis
Instructors: Dan Bauer & Doug Steinley
20 hours
Applied Measurement Modeling
Instructors: Patrick Curran & Greg Hancock
16 hours
Applied Qualitative Research
Instructors: Greg Guest & Emily Namey
20 hours
Machine Learning for Classification Problems
Instructor: Doug Steinley
12 hours
Machine Learning: Theory and Applications
Instructor: Doug Steinley
20 hours
Introduction to Sample Size Planning for Statistical Power
Instructor: Samantha Anderson
9 hours
Applied Research Design Using Mixed Methods
Instructor: Greg Guest
8 hours
Introduction to Data Visualization in R
Instructor: Michael Hallquist
16 hours
Introduction to Quantitative Meta-Analysis
Instructor: Tasha Beretvas
16 hours
Analyzing Intensive Longitudinal Data
Instructors: J-P Laurenceau & Niall Bolger
20 hours