Introduction to Multilevel Modeling (MLM)

Introduction to Multilevel Modeling (SEM)

A 3-day seminar introducing multilevel modeling for analyzing hierarchically organized data.

Overview: Everything is nested, so you need something more than multiple regression or analysis of variance to get the job done! Nested data structures can include students within classrooms, professionals within corporations, patients within hospitals, or repeated observations from the same person. Multilevel modeling (MLM) is built to handle this kind of data. You will use real datasets and the R software environment to learn how to analyze multilevel data sets and interpret results of multilevel models.

Topics include:

  • Review of regression and methods of handling nested data
  • Random-intercept and random-slope models
  • Testing and interpreting interactions in multilevel models
  • Cross-sectional and Longitudinal multilevel models
  • Multilevel models for binary outcomes
  • Cross-classified random effects modeling

Note: This course will focus primarily on with a single outcome variable.  As such, this course (in combination with a course in SEM Foundations) would provide an ideal introduction to the foundations necessary to prepare for the advanced Summer Stats Camp course, Multilevel SEM with xxM,

London Stats Camp: October 18 – 20, 2019
Hilton Paddington London

Enrollment is open to public, students, graduates and professionals. Save a seat today, pay later.

Payment Options

Seminar Venue: Hilton Paddington London
146 Praed Street, London, W2 1EE, United Kingdom
Maps and Directions
TEL: +44-207-850-0500 FAX: +44-207-850-0600

Book your room online individually on the dates required and at best available rates online. No group code is required.


Hilton Website

Heathrow is the closest transit and there is a Heathrow Express train that goes from the airport to the Paddington station which is where the Hilton is located.

Lunch and drinks including coffee, tea, and water will be provided daily. 

Question? Please contact us for more info or visit our FAQ page.

Seminar fee includes all materials, downloads, software access, training, refreshments and access to a recorded video of seminar:
$1,295 Faculty/Professional or
$945 Student/Post-Doc


Please select from our current fall course list

Seminar Audience

Participants from a wide variety of fields will benefit from the seminar, including sociology, psychology, education, human development, marketing, business, biology, medicine, political science, and communication.

Learning Objectives

After engaging in course lectures and discussions, as well as completing the hands-on practice activities with real data, participants will be able to:

  • Acquire an understanding of multilevel modeling techniques as applied in the educational, social, health, and behavioral sciences.
  • Manage and clean multilevel data for analysis.
  • Specify, estimate, evaluate, and compare different multilevel models using R software.
  • Interpret and present the results of a multilevel modeling analysis.
  • Critically evaluate applications of multilevel modeling in scientific studies.
  • Become acquainted with multilevel modeling for binary outcomes and for non-purely hierarchical data

Participants will also complete the course with a foundation for future learning about multilevel modeling and knowledge about available resources to guide such endeavors.

Seminar Prerequisites


  • 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 in binary logistic regression
  • At least limited experience using R

No level of proficiency beyond basic awareness is assumed for skills related to:

  • Multilevel Modeling.
  • Advanced mathematical or statistical topics such as matrix algebra or likelihood theory.


FridayOctober 18, 2019
9:00-9:30Welcome and introductions
9:30-10:45Introduction to Multilevel Modeling and Basics of R
10:45-11:00Snack and refreshment break
11:00-12:30Methods of handling nested data
12:30-13:30Lunch break
13:30-15:00Random effects
15:00-15:15Snack and refreshment break
17:00-19:00Social “hour” for Hilton hotel guests
SaturdayOctober 19, 2019
9:00-10:45Estimation and model building
10:45-11:00Snack and refreshment break
11:00-12:30Centering and contextual effects
12:30-13:30Lunch break
13:30-15:00Longitudinal Models
15:00-15:15Snack and refreshment break
15:15-17:00Longitudinal Models (continued)
SundayOctober 20, 2019
9:00-10:45Three-level and cross classified models
10:45-11:00Snack and refreshment break
11:00-12:30Binary outcomes
12:30-13:30Lunch break
13:30-15:00One-on-one consultations with instructor
15:00-15:15Snack and refreshment break
15:15-17:00One-on-one consultations with instructor

Instructor: Terrence Jorgensen Ph.D.

Dr. Terrence D. Jorgensen is an Assistant Professor at the University of Amsterdam. Terrence received his PhD in Quantitative Psychology from the University of Kansas in 2015, where he first joined Stats Camp as a counselor in 2011. Terrence teaches graduate courses in regression, ANOVA, and structural equation modeling (SEM). His methodological research interests include psychometrics (namely, testing measurement equivalence / invariance and detecting differential item functioning [DIF]), resampling methods (permutation, bootstrap, Monte Carlo simulation), Bayesian inference, planned missing data designs, and statistical programming.  Terrence’s current research project aims to integrate the social relations model (SRM) with SEM.  Terrence also maintains the R package semTools, to provide advanced methods via user-friendly software.

Software and Computer Support

If you are already reasonably familiar with regression analysis and you need to learn how to apply similar analyses to hierarchically structured data, this seminar is for you. The statistical environment R will be used for instruction, so we recommend some experience with R before taking this 3-day advanced seminar (e.g., by attending our summer institute on R Programming for Data Science, or the online DataCamp course). Specifically, this seminar will support the R package lme4. Only limited assistance will be available for questions related to other multilevel modeling packages.

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. However, the software used for instruction (R and RStudio) are free to downloaded from and, respectively. Additional directions will be shared with enrolled participants.

Seminar Files

Below are links to seminar files for those who enrolled in the seminar. Please download these files onto your computer on the first day of the seminar. The files are password protected to respect the intellectual property rights of the instructors. By using your login information, you agree not to share your login information or the content protected by it.

Seminar files and downloads will be posted on the first day of class.

Seminar Certificate

Upon completion of the seminar you may request an official Stats Camp print-ready PDF certificate.  Please contact us here to request a digital copy.

Why Should You Attend?

  • Get 1 on 1 Consultation With Instructor
  • Professional Networking
  • Peer Socializing
  • Collaboration
  • All Seminar Resources