In this Stat’s Amore Training, Marc Diener will help you make sense of the strange terms and symbols that you find in studies that use multilevel modeling (MLM). You’ll learn about the basic ideas behind MLM, different MLM models, and a close look at one particular model, known as the random intercept model. A running example will be used to clarify the ideas and the meaning of the MLM results.
Do the words “multilevel modeling” strike fear into your heart? Sure, they sound fancy, but they don’t have to be so scary. Journal editors are increasingly asking researchers to analyze their data using this particular approach, and for good reason.
In the real world in which researchers work, data are often “nested.” A classic example is when an investigator collects data on individual students, and these individual students attend different schools. If you use classical data analysis methods, you could end up lumping the data across the different schools. By doing this, you lose two important abilities. First, you can’t look at whether the school that students attend helps account for important associations between your variables. Second, you will understate the real variance, leading to biased standard errors and p-values.
About the Instructor
Marc Diener, PhD, maintains an independent clinical and research/statistics consulting practice and is an Associate Professor in the Clinical Psychology Doctoral Program at Long Island University—Post. In his practice, he provides psychological testing; individual psychotherapy; and clinical, research, and statistics consultation. He has published widely, including peer-reviewed journal articles and book chapters. He serves as a consulting editor for several journals, and his professional presentations include peer-reviewed and invited talks. He earned his doctorate in clinical psychology from Adelphi University and trained at Bellevue Hospital and St. Luke’s Roosevelt Hospital Center. He completed a postdoctoral fellowship at The Addiction Institute of New York/St. Luke’s Roosevelt Hospital Center. Prior to Long Island University—Post, he was a faculty member at the American School of Professional Psychology, Washington, DC. He is a Fellow in the Division of Independent Practice of the American Psychological Association.
Not a Member Yet?
It’s never too early to set yourself up for successful analysis with support and training from expert statisticians.
Just head over and sign up for Statistically Speaking.
You'll get access to this training webinar and 85+ other stats trainings — plus the expert guidance you need to progress with live Q&A sessions and an ask-a-mentor forum.