Multilevel Modeling

A 2-Day Seminar
Taught by Tenko Raykov, Ph.D

Read 11 reviews of this seminar.

Researchers in the behavioral, social, biomedical, business and economics disciplines often collect data that have a hierarchical structure. Patients are nested (clustered) within treatment centers, employees are nested within firms, respondents are nested within cities, students are nested within schools, and so on. As a consequence of this nesting, the observations in the data set are not statistically independent, thus violating a basic assumption of standard methods of analysis. Ignoring the nesting effect and proceeding with conventional, single-level methods of analysis (like linear regression) can yield highly misleading results. That’s because traditional methods produce standard errors that are typically too small, leading to confidence intervals that are too short and p-values that are too low.

This two-day seminar provides a thorough introduction to multilevel modeling, a statistical framework that accounts for the nesting effect and avoids these problems, as well as those associated with earlier methods of aggregation and disaggregation. Throughout the seminar, many empirical examples are drawn from the behavioral, clinical, educational and economics disciplines. The popular software package Stata is used for all the examples, along with a detailed discussion of the command syntax and intepretation of the output.

Participants in this seminar can expect to come away with:

1.  A nuanced understanding of the conceptual foundations and basic mathematical formulation of the multilevel model.
2.  The ability to understand, interpret and explain the output from multilevel modeling software.
3.  An appreciation of the advantages and disadvantages of multilevel modeling as compared with other approaches to nested data.
4.  Practical tools and strategies for developing and testing multilevel models.
5.  The ability to extend the multilevel model to dichotomous outcomes.
6.  A clear understanding of the differences between fixed and random effects.

 Who should attend?

To benefit from this seminar, you should have the equivalent of two semesters of statistics: a good introductory course with some treatment of probability and random variables, and a course on linear models. Some knowledge of logistic regression will also be helpful but not essential.

Schedule and materials

The class will meet from 9 to 4 each day with a 1-hour lunch break. 

Participants receive a bound manual containing detailed lecture notes (with equations and graphics), examples of computer printout, and many other useful features. This book frees participants from the distracting task of note taking. 

Registration and Lodging

The fee of $895 includes all course materials. If registration is completed by February 22, the fee is discounted to $795.  

Lodging Reservation Instructions

A block of rooms has been reserved at the Club Quarters Hotel, 1628 Chestnut St., Philadelphia, PA at a nightly rate of $137 for a Standard room. This hotel is about a 5-minute walk from the seminar location.  To make a reservation, you must call 203-905-2100 during business hours and identify yourself by giving the group code STA321. For guaranteed rate and availability, you must make your reservation by February 19, 2013. 

Seminar outline

1. Resources for the seminar.
2. Why do we need multilevel modeling (MLM)? Why are aggregation and disaggregation unsatisfactory?
3. The beginnings of MLM

  • why what we already know about regression analysis is so useful
  • centering of predictor variables.

4. The intra-class correlation coefficient – Do we really need a multilevel model?
5. How many levels? – Proportion of variance at the third-level and how to evaluate it.
6. Robust modeling of lower-level variable relationships in the presence of clustering effects.
7. What are mixed models, what are they made of, and why are they useful?
8. A new look at random regression models – a general class of mixed/multilevel models of great utility

  • restricted maximum likelihood (REML) estimation,random regression models,
  • multiple random slopes
  • fixed effects, random effects, and total effects,
  • numerical issues and possible problems,
  • nested levels (higher-order nesting).

9. Mixed models with discrete response variables – what to do when the outcome is not continuous? 

  • why do we need another modeling approach?
  • random intercept model with discrete outcome,
  • random regression model with discrete response
  • model choice with discrete outcome.

10. Applications of multilevel modeling in complex design studies.
11. Conclusion and outlook. 


This seminar will use Stata for all examples, but prior knowledge of Stata is not essential. You are welcome to bring your own laptop computer, and outlets will be provided at each seat.  No internet service will be provided, however.  

Comments from recent participants

“Excellent approach that factors in both contextual and technical issues in a relatively easy to comprehend way.”
  Fatou Jah

”Knowledgeable teacher gives hands-on or practical examples in explaining the theory, which should be the most effective way of learning a new theory or technique. Besides, the teacher provides his insight on many statistics-related issues along the teachings, which is precious and valuable.”
  Robert Yu, University of Texas, MD Anderson Cancer Center

“Dr. Raykov provided an excellent conceptual understanding of the multilevel and mixed effects models. Within the limited time span, he also covered a great deal of software syntax for the participants. For a 2-day workshop, Dr. Raykov did an outstanding job! The workshop included both underlying theory and actual examples, creating a very sound foundation for participants to go on to more advanced textbooks/workshops of MLM.”

“This is a course which is not only good for starter for STATA but also for people who have other comparable software experience.”
  Linda Yu

“An excellent workshop. Well worth the money. In two days I learned more than in one semester.”

“In the first day of the course, Dr. Raykov cleared up two questions that I have had for a couple of years.”
  Charles Day, SAMSHA

“The course provided a great introduction to MLMs. You leave understanding the ideas behind the models and equipped with code to actually use the methods. The instructor was top notch, employing excellent pacing, examples, anecdotes and thorough notes to use as a resource.”
 Jennifer Givens, University of Utah

 “Before taking this workshop, I read broadly on multilevel modeling. I quickly realized that the literature, as it develops in different disciplines, uses jargon that tends to be confusing. The workshop helped tremendously to clarify key concepts and the instructor’s knowledge of how MLM has evolved in different fields, helped tie things together. I would highly recommend Tenko’s workshop for anyone wishing to pursue MLM techniques in their own disciplinary field.”

 “The instructor was top-notch – very knowledgeable, responsive, knew answers to almost every question. It’s hard to find someone that versatile.  There was a good mix of theory and practical applications. I feel empowered to go build multilevel models   and feel confident that I will be successful at programming and troubleshooting these models.”

“Dr. Raykov is a very insightful statistician. He explained the essence of multilevel modeling in both mathematical and commonsensical ways.  The way he linked MLM with structural equation modeling and time-series cross-sectional analysis was both illuminating and pedagogical.”

“I really enjoyed this workshop because attendees come from different backgrounds and all with highly professional training. Questions raised during class are very good and induce a lot of thinking.”
 Sherry Yan, Geisinger Center for Health Research