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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

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.
Best Statistics Training Course Online

Anna Yu Lee, PhD, MPH, MA, Counselor/Therapist

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

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.
Best Statistics Training Course Online

Amy K. Syvertsen, Ph.D., Applied Developmental Scientist

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

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 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

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

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.
Best Statistics Training Course Online

Katie Paschall, Ph.D., Senior Research Scientist at Child Trends

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

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

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!
Best Statistics Training Course Online

Kris Carlson, Ph.D., Sandia National Laboratories

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

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!
Best Statistics Training Course Online

Chen Zhang, Ph.D., Faculty University of Memphis

IN PERSON – 5-day Statistics Short Course

Multivariate Modeling Seminar Overview:

An introductory 5-day course on using R software for common analytic methods in behavioral and social sciences. Topics covered include, regression, mediation and moderation, multilevel modeling (MLM), factor analysis and structural equation modeling (SEM).

Seminar Topics:

  • Introduction to R software and importing data into R
  • Fitting regression models in R
  • Testing mediation and moderation models in R
  • MLM in R
  • Factor analysis and SEM in R

Seminar Description:

This seminar is intended to introduce participants to popular multivariate statistical methods using the R software program. R is a free, open-source software program which continues to grow in popularity across a wide variety of fields. R provides cutting edge functionality for most popular multivariate analyses used by researchers in behavioral and social sciences.

This seminar will help you begin to learn how to analyze multivariate models using R. The seminar will cover regression, mediation, moderation, multilevel, factor and SEM models in R. 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 seminar will focus on best practices approaches to model specification and interpretation across all covered methods. Coverage of confirmatory factor analysis and SEM will use the lavaan package.

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.

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:

Multivariate Modeling

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:

  • Acquire an understanding of modeling techniques using R as applied in the educational, social, health, and behavioral sciences
  • Specify, estimate, evaluate, and compare regression models using R software
  • Specify, estimate, evaluate, and compare mediation and moderation models using R software
  • Specify, estimate, evaluate, and compare multilevel models using R software
  • Specify, estimate, evaluate, and compare factor analysis and SEM models using R software

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

Seminar Prerequisites:

Required:

  • 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 using R

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

  • Factor Analysis, SEM, or MLM.
  • Advanced mathematical or statistical topics such as matrix algebra or likelihood theory.

Software and Computer Support:

Required:

  • 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 using R

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

  • Factor Analysis, SEM, or MLM.
  • Advanced mathematical or statistical topics such as matrix algebra or likelihood theory.

Multivariate Modeling Seminar Audience:

The ideal audience for our statistical methods training course in multivariate modeling would be:

  1. Data analysts and data scientists who have a solid foundation in statistical methods and want to learn advanced techniques for analyzing complex datasets with multiple variables.
  2. Researchers in various fields who have some background in statistical analysis and want to learn how to analyze data with multiple variables to draw meaningful conclusions.
  3. Business analysts and decision-makers who want to use multivariate analysis to understand the factors that affect business performance, customer behavior, or market trends.
  4. Engineers and scientists who have some familiarity with statistical analysis and want to learn how to model and analyze systems with multiple variables, such as chemical processes, mechanical systems, or biological systems.
  5. Healthcare professionals who have a background in statistical analysis and want to learn how to analyze data from clinical trials or patient records to evaluate treatment effectiveness or identify risk factors for diseases.

In general, the ideal audience for the Stats Camp statistical methods training course in multivariate modeling would be looking to expand their skills and learn more advanced techniques for analyzing complex datasets with multiple variables.

Seminar Files

Instructor will provide password on first day of seminar.

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 12, 2023
9:00-9:30 Welcome and introductions
9:30-10:45 Introduction to R
10:45-11:00 Rest Break
11:00-12:30 Basics of R and reading data into R
12:30-1:30 Rest Break
1:30-3:00 Regression with R
3:00-3:15 Rest Break
3:15-5:00 Regression with R (continued)
Tuesday June 13, 2023
9:00-10:45 Mediation with R
10:45-11:00 Rest Break
11:00-12:30 Moderation with R
12:30-1:30 Rest Break
1:30-3:00 Combining Mediation and Moderation with R
3:00-3:15 Rest Break
3:15-5:00 Missing Data Handling with R
Wednesday June 14, 2023
9:00-10:45 MLM with R
10:45-11:00 Rest Break
11:00-12:30 MLM with R (continued)
12:30-1:30 Rest Break
1:30-3:00 Longitudinal MLM with R
3:00-3:15 Rest Break
3:15-5:00 Longitudinal MLM with R (continued)
Thursday June 15, 2023
9:00-10:45 Exploratory Factor Analysis (EFA) with R
10:45-11:00 Rest Break
11:00-12:30 Confirmatory Factor Analysis (CFA) with R
12:30-1:30 Rest Break
1:30-3:00 Multiple group CFA with R
3:00-3:15 Rest Break
3:15-5:00 Multiple group CFA with R (continued)
Friday June 16, 2023
9:00-10:45 SEM with R
10:45-11:00 Rest Break
11:00-12:30 SEM with R
12:30-1:30 Rest Break
1:30-3:00 One-on-one consultations with instructor
3:00-3:15 Rest Break
3:15-5:00 One-on-one consultations with instructor

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