Transitioning to R for MLM

A hands-on guide to transitioning from other software (e.g., SPSS, SAS, Stata, or HLM) to the open-source R platform for conducting multilevel modeling, also called mixed-effects modeling, hierarchical linear modeling, and random coefficient modeling.

Instructor:
Jeffrey Girard, PhD (University of Kansas)

Workshop Dates and Times:
Tuesday, June 18, 2024, 12:30pm to 4:30pm ET
Wednesday, June 19, 2024, 9:30am to 4:30pm ET

Workshop Format:
1½ Day Synchronous Online Workshop

R is a popular software option for analyzing, wrangling, and visualizing data in the social, behavioral, and medical sciences. It is completely free, runs on all major platforms (i.e., Windows, Mac, and Linux), and offers a rich catalog of tools and techniques that are updated frequently. It is an excellent choice for researchers who conduct statistical analyses and is often the first software to support exciting new modeling approaches.

This one-and-a-half-day workshop is aimed at helping researchers transition to R from other software packages (e.g., SPSS, SAS, Stata, or HLM) for conducting multilevel modeling, also called linear mixed modeling, mixed-effects modeling, hierarchical linear modeling, and random coefficient modeling. It assumes that learners already know the concepts and theory underlying these techniques (e.g., from a graduate MLM course or textbook, perhaps using a different software package) and is not intended as a substitute for such a course or textbook. It also assumes that learners have a basic understanding of how R works (e.g., from the Introduction to R for Researchers workshop).

The knowledge gained in this workshop is designed to be modernized and tailored to the needs of researchers in the social, behavioral, and medical sciences. It will be invaluable for other workshop offerings that focus on more advanced techniques in R.

What you’ll learn

  • Building Blocks

    Prepare data for analysis, Build null models, and Assess clustered residual dependency

  • Main Models

    Fit random intercepts and slopes, Estimate and visualize group-level effects, and Troubleshoot errors

  • Extensions

    Adjust random correlations, Model nested and crossed levels, and Predict non-normal outcomes

Registration Options

Transitioning to R for Multilevel Modeling

  • Professional
  • $449
  • Baseline Price for Faculty,
    Staff, and Other Professionals
  • Click Register Below
  • Trainee
  • $449 $299
  • 33% Discount for
    Students and Postdocs
  • Use code "TRAINEE" at Checkout

Combo 1: Transitioning to R for Multilevel Modeling + Transitioning to R for Statistics

  • Professional
  • $899 $719
  • Baseline Price for Faculty,
    Staff, and Other Professionals
  • 20% Combination Discount
  • Click Register Below
  • Trainee
  • $719 $479
  • 33% Discount for
    Students and Postdocs
  • 20% Combination Discount
  • Use code "TRAINEE" at Checkout

 FAQs

  • This workshop was custom built for researchers in the social, behavioral, and medical sciences who have completed an introductory MLM course in graduate school and are looking to transition to R from other software packages (e.g., to modernize their statistical practices or take advantage of the many powerful features that R offers). Note that this workshop does not emphasize applications of MLM to longitudinal data, as there is a different workshop for that. This workshop is intermediate and appropriate for faculty, staff, and students at both the graduate and advanced undergraduate levels.

  • This workshop assumes that learners already have a good grasp on the ideas behind (i.e., theories and practice of) MLM. It also assumes that learners have a basic grasp of how R works (e.g., have completed the Introduction to R for Researchers workshop).

  • Registered learners will gain access to the Zoom link and passcode to attend the synchronous workshop, as well as video recordings of the lectures, downloadable slideshows, and example data files.