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1 FREE Night Included, Click Here to Book Your Room!

Venue Information: Embassy Suites By Hilton 1000 Woodward Pl NE, Albuquerque, NM 87102

Cancellation Policy:

If you cancel your registration at least two weeks prior to the day the course is scheduled to begin, you are entitled to a full refund (minus a processing fee of $50). If you cancel within the 14 days prior to the course you may transfer the full amount towards any future course or receive a full refund (minus a processing fee of $295).

In the unlikely event that Stats Camp Foundation must cancel a course, our team will do our best to inform you as soon as possible with more information. Students then have the option of receiving a full refund of the course fee or a full credit towards another future course. In no event shall Stats Camp Foundation be held responsible for any incidental or consequential damages that you may incur because of the cancellation. Course disclaimer. All courses include 365 days of asynchronous access after event.

*You must register prior to the event start, attendance is NOT mandatory. However; CE credits are only available if you attend live for the duration of the course. (Includes: On-Demand, Livestream and In-Person courses, all Stats Camp Retreats are in-person attendance only.)


what students are saying

I can strongly recommend the Stats Camp Summer course in Longitudinal Mixture Modeling. It is as systematic and comprehensive as the very best of the research methods courses I have participated in since I moved from business to academics 12 years ago. It has been an important tool box for pulling apart differing effects in subpopulations for the coming generation of social and behavioral science researchers, starting now!
Best Statistics Training Course Online

Alan R. Johnson, Ph.D., Senior Research Fellow at NORD University, Bodø, Norway

I can honestly say that for the first time in years I have been able to focus on myself and my research. I feel physically and mentally healthier than ever and I am excited about the cutting-edge knowledge and resources I am gaining in the rapidly evolving field of latent variable modeling. I am going to make it a goal to prioritize Statscamp for myself and graduate students on a yearly basis. Definitely recommend!
Best Statistics Training Course Online

Sarah D. Lynne-Landsman, Ph.D., Family, Youth & Community Sciences

I was impressed with the amount of material Dr. Todd Little and team were able to cover in Summer Camp. The instructors moved at a pace appropriate for the participants, adapted the materials as we went along to accommodate this pace, and still offered individual consultations. I am confident that I can take everything I learned, from the basic to the advanced topics & employ them independently in my own research.
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Katie Paschall, Ph.D., Senior Research Scientist at Child Trends

Thank you to Dr. Todd Little and his team for facilitating such a great statistical methods training workshop in Albuquerque. I absolutely got what I needed and was energized in my work when I returned to Cleveland. This was a wonderful experience that I will be sure to share with my colleagues here at CWRU. Now I am looking forward to mediation this summer in Albuquerque! Who knew I would be excited for more stats!
Best Statistics Training Course Online

Leigh-Ann Sweeney, Ph.D., Lecturer and Health Service Researcher

I participated in the SEM: Foundations and Extended Applications course earlier this summer. It was such a wonderful statistics training opportunity that has, already, found lots of applications in various grant proposals and analyses. As I’ve said to several colleagues since, Stats Camp has a special ability to take something that prior to my arrival seemed overwhelming and complicated and make it seem so do-able.
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Amy K. Syvertsen, Ph.D., Applied Developmental Scientist

The highlight of the summer break was attending ‘Stats Camp,’ an educational camp in Albuquerque New Mexico that provides advanced-level training in Statistics. The 5-day class I took (‘SEM with Mplus’) passed by quickly, as an information-packed series of lectures, hands-on examples, personal consultations, and jokes. Classes were small, lectures succinct/direct, and training content based on each individual student requests.
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Anna Yu Lee, PhD, MPH, MA, Counselor/Therapist

Stats Camp was the most useful statistical training I’ve ever had. The instructors are down to earth and practical in their teaching style and the classroom environment was relaxed and non-threatening, which is necessary for such a potentially daunting topic. In particular, the one-on-one private consultation with my own data was invaluable, I highly recommend signing up for the Summer Stats Camp in Albuquerque!
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Kris Carlson, Ph.D., Sandia National Laboratories

The Summer Stats Camp training institute provides a wonderful opportunity for researchers and data analysts to learn the basic foundations of SEM as well as some advanced applications and research opportunities that SEM can facilitate. Dr. Little provides personable “hands-on”instruction in a relaxed and enjoyable environment. I highly recommend this summer institute to faculty and graduate students alike!
Best Statistics Training Course Online

Paul Schrodt, Ph.D., Professor and Director of Graduate Studies

I took both Foundations of SEM and Longitudinal SEM last summer and I have to say this has been one of the most useful learning experiences of my life. The courses were excellent! Everything was explained in a clear fashion with plenty of time for questions and practice. Learning was fun and the teaching happened at multiple levels, such that everyone would have a lot of knowledge gain regardless of their level of expertise.
Best Statistics Training Course Online

Rodica Damian, Ph.D., Associate Professor University of California, Davis

Stats Camp is the place for a meeting of the minds and an opportunity to sit down and sort through complex ideas with people who can guide you, side-by-side, through the sticking points so you can get back into the flow. It’s amazing that something like this exists. Dr. Little has given the world a tremendous gift with Stats Camp. I walked in knowing nothing substantial and walked out delighted and better skilled.
Best Statistics Training Course Online

Benjamin Theisen, Ph.D., Business Psychology Consulting Group

The Stats Camp instructor’s clear and practical presentation of material that was once intimidating to me has uncovered a powerful analytic tool. I feel comfortable that I’ve learned the correct application of SEM Foundations and Extended Applications from experts in the field. At the same time, I was introduced to cutting edge statistics techniques and I understand the advantages of their practical use and application.
Best Statistics Training Course Online

Jenny Tehan, Ph.D., Department of Psychology University of Akron

The Stats Camp instructors have an unmistakable dedication to research methods and data analysis of the very highest quality-but are remarkably balanced in their very obvious efforts to connect with others on a professional and personal level as very likable and real people. I really enjoyed the networking opportunities that the breakout sessions provided and will be returning for another Summer Camp soon!
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Chen Zhang, Ph.D., Faculty University of Memphis

The Stats Camp expert instructors were clear, concise, and helpful in addressing questions. Before attending, I was concerned that I would have trouble truly understanding all of the concepts and material in such a short time, but the instruction was fantastic and not overwhelming. I particularly found it advantageous to stay on-site at the Embassy Suites so I could participate in all of the after hours networking events.
Best Statistics Training Course Online

Spiros Tzivelekis, Ph.D., GHE Director - Amgen

IN PERSON – 5-day Multilevel Modeling Statistics Short Course

Seminar Overview:

An intermediate 5-day course introducing multilevel modeling for analyzing hierarchically organized data. 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.

Seminar Topics:

  • 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: MLM is sometimes referred to as mixed-effects modeling, hierarchical linear modeling, or random coefficients modeling. This course will focus primarily on with a single outcome variable.  As such, this course (https://www.statscamp.org/courin 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.

Seminar Description:

This course is designed to provide theoretical and applied understandings of multilevel modeling. The fundamentals of multilevel modeling are taught by extending knowledge of regression analyses to designs involving a nested data structure. Nested data structures include, for example, students within classrooms, professionals within corporations, patients within hospitals, or repeated observations from the same person. In each of these cases and many more, the data are hierarchically arranged and may require methods beyond multiple regression or analysis of variance. These methods fall under the heading of multilevel modeling, which is also sometimes referred to as mixed modeling, hierarchical linear modeling, or random coefficients modeling.

This course will help you begin to learn how to analyze multilevel data sets and interpret results of multilevel modeling analyses. Cross-sectional and longitudinal models, the most common multilevel modeling applications, are featured in the seminar. Using real datasets provided in the seminar, participants will learn how to use the R software program to analyze data and interpret results. Further, the course will emphasize proper interpretation of analysis results and illustrate procedures that can be used to specify multilevel models. Coverage of multilevel models for binary outcomes and cross-classified random effects modeling will also be included.

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.

Instructor: Alex Schoemann, Ph.D.

Multilevel Modeling in R

Dr. Alexander M. Schoemann, is an Alex Schoemann, Ph.D. is 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 for advanced methods including applications for power analysis for mediation models (http://marlab.org/power_mediation/).

APA Continuing Education Credits:

Multilevel Modeling in R Statistica Software

This course offers 29 hours of Continuing Education Credits. Stats Camp Foundation is approved by the American Psychological Association to sponsor continuing education for psychologists. Stats Camp Foundation maintains responsibility for this program and its content.

Seminar Includes:

Materials, downloads, recorded course video viewable for up to one year.

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:

  • Identify the basic functions of R that are relevant to multilevel modeling.
  • Understand the principles behind multiple linear regression.
  • Describe the methods of handling nested data.
  • Modify regression models by adding predictors and random effects.
  • Apply methods of centering.
  • Evaluate models with interactions.
  • Conduct multiparameter tests.
  • Make informed decisions about model selection.
  • Evaluate longitudinal models.
  • Implement alternative error structures.
  • Evaluate multiple group models.
  • Understand the roles sample size and power play in a multilevel framework.
  • Evaluate multivariate models.
  • Evaluate three-level models.
  • Evaluate cross-classified random effects models.
  • Evaluate models with categorical outcome variables.

Multilevel Modeling 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.

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.

Note: Limited examples will also be provided in SPSS and SAS but the majority of the course will be taught using R.

Seminar Audience:

Coming Soon…

Seminar Files

Below are links to seminar files for those who enrolled in the seminar. Please download these files onto your computer before 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.

Instructor will provide password on first day of seminar:
Click Here to Access The Multilevel Modeling Seminar Files

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.

Monday June 5, 2023
9:00-9:30 Welcome and introductions
9:30-10:45 Introduction to multilevel modeling and basics of R
10:45-11:00 Rest Break
11:00-12:30 Review of multiple linear regression
12:30-1:30 Rest Break
1:30-3:00 Methods of handling nested data
3:00-3:15 Rest Break
3:15-5:00 Adding predictors and random effects
Tuesday June 6, 2023
9:00-10:45 Centering
10:45-11:00 Rest Break
11:00-12:30 Interactions and contextual effects
12:30-1:30 Rest Break
1:30-3:00 Estimation
3:00-3:15 Rest Break
3:15-5:00 Multiparameter tests and model selection
Wednesday June7, 2023
9:00-10:45 Longitudinal models
10:45-11:00 Rest Break
11:00-12:30 Longitudinal models (continued)
12:30-1:30 Rest Break
1:30-3:00 Alternative error structures
3:00-3:15 Rest Break
3:15-5:00 Multiple group models
Thursday June 8, 2023
9:00-10:45 Power and sample size
10:45-11:00 Rest Break
11:00-12:30 Multivariate Models
12:30-1:30 Rest Break
1:30-3:00 Three-level modeling
3:00-3:15 Rest Break
3:15-5:00 One-on-one consultations with instructor
Friday June 9, 2023
9:00-10:45 Cross-classified random effects modeling
10:45-11:00 Rest Break
11:00-12:30 Cross-classified random effects modeling (continued)
12:30-1:30 Rest Break
1:30-5:00 One-on-one consultations with instructor

Please fill out and submit the form below to get instant access to sample course materials.

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