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Multivariate Statistical Modeling using R

June 12 @ 9:00 am - June 16 @ 5:00 pm MDT

| $945.00 – $1,695.00

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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/).

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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

Download Sample Slides and Preview Course Video

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

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