Data modeling for behavioral research bootcamp
A Two-Part Five-Day TOMNET Bootcamp
(Register for Either Part or for the Entire Bootcamp)
Start: TBD (May/June 2021)
End: TBD (May/June 2021)
Location: Arizona State University, Tempe, AZ 85281
Room: College Avenue Commons (CAVC) Room 559, 660 S College Avenue
Registration Fees (Early Bird Deadline: TBD)
Registration for the workshop is handled online via credit card payment. If you or your organization need an invoice to make the payment, please contact Megan Pratt at firstname.lastname@example.org. Alternative payment methods may be accommodated by special request. Workshop EARLY BIRD registration fees are as follows (valid through TBD):
|Workshop||Regular Attendee||Public Agency, Government, Non-Profit, University Attendee|
|Part 1: Machine Learning (3 days)||$995||$845|
|Part 2: Structural Equation Modeling (2 days)||$695||$545|
|Parts 1 and 2 Combined (5 days)||$1,495||$1,245|
Rates will increase by $200 per person after TBD. Discounted registration fees are available for multiple participants (more than two) from the same organization. Please contact Megan Pratt for details.
Note: All registrants (of either workshop or the entire bootcamp) will receive a free copy of the following reference book.
Grimm, K.J., N. Ram, and R. Estabrook (2017) Growth Modeling: Structural Equation and Multilevel Modeling Approaches. Guilford Press, New York, NY.
Workshop Sponsorship opportunities are available too.
For workshop sponsorship information and benefits, please contact Megan Pratt at email@example.com. Your sponsorship contributions will allow us to offer scholarships for student attendees. Your contributions will be prominently acknowledged.
TOP 10 REASONS TO ATTEND A WORKSHOP IN PHOENIX IN MAY/JUNE 2021
- It’s so hot you’ll want to stay indoors and learn the workshop material (achieving 100% attendance will be so easy).
- You can appreciate the meaning of “urban heat island effect” first hand.
- You will have a greater appreciation for global “warming”.
- You will feel the “warmth” of our welcome and affection every minute of every day.
- You can stay in a luxurious Scottsdale resort at unbelievably low prices.
- You’ll be able to brag to your friends and family for the rest of your life: I survived a Phoenix summer.
- You will receive a special Phoenix Summer Survival kit and Certificate of Accomplishment.
- There is so little traffic that you’ll start believing global warming could be a very effective travel demand management strategy.
- You’ll want to take a stroll so early in the morning that you can watch the beautiful sunrise every day.
- You’ll develop a greater appreciation for your own humid summers and harsh snowy winters back home!
- (BONUS) You can visit beautiful Sedona, Grand Canyon, and many other natural wonders of Arizona to cool off.
This five-day data modeling bootcamp consists of two parts.
Part 1: Machine Learning for Behavioral Modeling (May/June 2021)
The first three-day training workshop covers the theory and application of machine learning (data mining, statistical learning) and exploratory approaches to data analysis. In contrast to traditional hypothesis-driven approaches to analysis, machine learning enables investigators to assess the predictive value of various combinations of variables in a data set. Machine learning has emerged in recent years as a major area of statistical research and practice and is increasingly employed by psychologists and other behavioral scientists. Machine learning techniques are particularly useful for the analysis of very large data sets, as can arise in clinical, survey, psychometric and genomic research. These techniques are often a natural follow-up to standard multiple variable and multivariate analyses where investigators have either: (1) obtained significant results and seek to know whether there are other important patterns in the data; (2) obtained no notable results and wonder whether there are any important patterns to be found; or (3) developed questions that are too general or imprecisely formulated to be addressed through hypothesis testing. The goals of this workshop are to provide attendees an understanding of various machine learning approaches, how to assess the utility of each approach, how to evaluate the predictive power of each approach, and how to tailor models to obtain replicable results. The workshop will include both theoretical and practical hands-on exercises using R, which is freely available at cran.us.r-project.org. Topics covered include an introduction to R, cross-validation using k-fold cross-validation, linear and nonlinear regression models, splines and smoothing splines, multiple regression, basic variable selection approaches in multiple regression (e.g., best subset regression, forward selection), advanced variable selection approaches in multiple regression (e.g., regularized regression, multivariate adaptive regression splines), logistic regression and decision theory, classification and regression trees, and ensemble methods (bagging, random forests, and boosting).
Part 2: Structural Equation Modeling (May/June 2021)
The second part of the bootcamp constitutes a two-day workshop on Structural Equation Modeling. Structural Equation Modeling (SEM) techniques are used extensively in the social sciences to model behaviors. The strength of SEM lies in its ability to model a multitude of dependent variables simultaneously while explicitly considering error covariances across the equations that comprise the simultaneous equations model system. More importantly, SEM approaches are powerful methodological tools to consider attitudinal variables and constructs in behavioral modeling through the incorporation of latent variables that represent different attitudinal factors. By simultaneously embedding a factor analysis of attitudinal variables with a structural model of latent constructs, SEM is able to provide deep insights into behavioral relationships that connect attitudes and behavioral outcomes. This two workshop will cover the fundamentals of SEM including path analysis, exploratory and confirmatory factor analysis, latent variable path analysis, and multiple group analysis. The workshop will include both theoretical and practical hands-on exercises using R. Additional illustrations will be demonstrated using Mplus.
Dr. Kevin J. Grimm
The primary instructor of the workshop is Dr. Kevin J. Grimm, Professor in the Department of Psychology at Arizona State University. Dr. Grimm is an internationally renowned expert and authority in statistical modeling for behavioral research. Dr. Grimm received his B.A. in Mathematics and Psychology with a concentration in Education from Gettysburg College in 2000, and his M.A. and Ph.D. in Psychology at the University of Virginia in 2003 and 2006, respectively. In 2007, Dr. Grimm became an Assistant Professor in the Department of Psychology at the University of California at Davis. In 2011, he was promoted to Associate Professor. In 2014, Dr. Grimm moved to the Department of Psychology at Arizona State University. Dr. Grimm was promoted to the rank of Full Professor effective August 2016.
Grimm’s research focuses primarily on longitudinal methods for the study of change at the individual and group-level, including research into nonlinear change models, growth mixture models, and latent change score models. His current research focuses on data integration, the specification of growth models for binary and ordinal outcomes, model selection in finite mixture modeling, and the development and application of machine learning techniques for psychological science. He is the author of Growth Modeling: Structural Equation and Multilevel Modeling Approaches (2017; Guilford) and has a book titled Exploratory Data Mining for Social and Behavioral Scientists (with Ross Jacobucci) that is under contract with Guilford. He is the 2017 recipient of the Cattell Award from the Society of Multivariate Experimental Psychology for early career contributions to multivariate experimental psychology. Dr. Grimm teaches undergraduate and graduate quantitative courses at ASU, including Longitudinal Growth Modeling, Data Mining, and Structural Equation Modeling. He also teaches workshops sponsored by the American Psychological Association’s Advanced Training Institute and Statistical Horizons.
The workshop offers a comprehensive and state-of-the-art/practice coverage of machine learning methods for behavioral modeling. The workshop content is organized as follows:
Introduction to Machine Learning
Introduction to R
Regression & cross-validation (Bias / Variance Trade off)
Multiple Regression and Best Subsets Regression
Forward selection, Backward elimination, and Stepwise regression
Spline Models and Smoothing Splines
Tutorial: Hands-on data analysis with R
Multivariate Adaptive Regression Splines
Classification & regression trees
Tutorial: Hands-on data analysis with R
Bagging & Random Forests
Introduction to Support Vector Machines (SVM)
Tutorial: Hands-on data analysis with R
Introduction to Structural Equation Modeling and Model Expectations
Confirmatory Factor Analysis
Tutorial: Performing path analysis and confirmatory factor analysis using R
Latent Variable Path Analysis
Multiple Group Analysis
Introduction to More Advanced Topics in Structural Equation Modeling (e.g., modeling discrete and ordinal variables)
Tutorial: Performing latent variable path analysis and multiple group analysis
The workshop will be held in College Avenue Commons (CAVC) (Room 559), a state-of-the-art collaborative learning environment that is home to TOMNET and the School of Sustainable Engineering and the Built Environment at Arizona State University on the Tempe Campus. The building is located at the northwest corner of S College Avenue and E 7th Street. The official address of the building is 660 S College Avenue, Tempe, Arizona 85281, USA. Parking is available in the Fulton Center Parking Garage, located just across from CAVC at the same intersection. The building may also be accessed by light rail, with a light rail station located just a short walk away at the intersection of S College Avenue and Veterans Way. This light rail station is located at the Tempe Transportation Center.
A map showing the location of the building, parking garage, and light rail station is available here.
Travel and Accommodation
Tempe is located in the Greater Phoenix Metropolitan area. Arizona State University is located just 15-20 minutes from Phoenix Sky Harbor International Airport. An alternative airport is the Phoenix-Mesa Gateway Airport. Travelers coming into Phoenix Sky Harbor International Airport will be able to use the light rail to reach the workshop venue. Alternative ground transportation options including ride-hailing services (Uber, Lyft), regular taxi services, and Supershuttle services. Travelers wishing to rent a car should follow the signs to the Rental Car Center; all major rental car companies serve the Greater Phoenix market. Parking on the ASU campus costs $15 per day. In the spirit of promoting sustainable transportation mode use, the workshop does not validate or cover parking charges. Attendees are responsible for parking charges if they choose to drive and park.
Accommodation is available for participants in a number of hotels located within a short distance of the workshop location, and all along the light rail line. Workshop participants are responsible to make their own hotel accommodation arrangements. Accommodation is also available through AirBnB, VRBO, HomeAway, and other vendors. A list of candidate hotels is available here. Please note that hotel costs are quite inexpensive during the hot summer months. Attendees may wish to explore staying in and enjoying the hospitality of luxurious resorts in the Greater Phoenix metro area at very modest prices.
For information and assistance, please contact any of the following:
Assistant Director, TOMNET
Administrative Coordinator, TOMNET
|Ram M. Pendyala
We are requesting pre-registration so that we have an estimate of number of attendees and can plan/prepare accordingly. Please provide the information requested in the form as accurately as possible.
All workshop registrants will receive a binder of course materials. Please register for the workshop as soon as possible so that appropriate arrangements can be made and course binders can be prepared in time. Payment is required before attendees can participate in and attend the workshop. Attendees participating in this professional development workshop will receive a certificate of attendance (but will NOT receive official Arizona State University credit, grade, or official transcript). Complete 100% attendance is required to receive the TOMNET certificate of participation. The certificate will document the number of classroom instructional hours.