Multilevel Modeling with R:
A oneweek (4.5 day) workshop on Multilevel Modeling Using R will be held at the University of Connecticut from Monday, June 11, through Friday, June 15, 2018. This workshop covers the basics and applications of multilevel modeling with extensions to more complex designs. Participants will learn how to analyze both organizational and longitudinal (mostly growth curve) data using multilevel modeling and to interpret the results from their analyses. Although the workshop does not require any prior knowledge or experience with multilevel modeling, participants are expected to have a working knowledge of multiple regression as well as some experience using statistical software (such as SPSS, SAS, R, Stata). Instruction consists of lecture, computer workshops, and individualized consultations. The emphasis will be practical with minimal emphasis on statistical theory, but those seeking more statistical information can arrange an individualized session with the instructors. A teaching assistant will also be available for consultation and assistance.
All analyses will be demonstrated using R. We can also provide setups in HLM for some of the analyses that we present. Instruction will consist of lectures, computer demonstrations of data analyses, and handson opportunities to analyze practice data sets using R. The workshop emphasizes practical applications and places minimal emphasis on statistical theory. The workshop takes place in a computer lab, so you do not need to bring a laptop. No prior familiarity with R is required, but if you have never used R and want to gain a general proficiency working with data in R, we encourage you to take the twoday DATIC Intro to R and RStudio workshop held on Thursday, June 7, through Friday, June 8, 2018. In this Multilevel Modeling workshop we will focus solely on running multilevel organizational and longitudinal models in R. Several R setups will be given for data organization, analysis, and writeups. Although prior experience with R is not required, it is certainly helpful. Also in meetings with individual participants, alternative programs and approaches (e.g., SPSS, HLM, MLwiN, SAS, Stata, and Mplus) can be discussed.
Logistical details: The Multilevel Modeling workshop runs MondayThursday from 95 and Friday from 912. A light continental breakfast is provided every morning. There is also a closing group lunch on Friday from 12:001:00 pm.
Benefits:
The following materials and events are included in the cost of the workshop:
 Tape bound workbook with workshop outline, computer setups and outputs
 R programs to assist in the writeups of the results of multilevel analyses
 Meals: Continental breakfast each morning, complimentary luncheon Friday
Day 1: Monday, June 11
8:30 – 9:00  Continental Breakfast, 319 Gentry 
9:00 – 9:15  Introduction to Multilevel Modeling – overview of the week 
9:15 – 10:45  Basics of Multilevel Modeling
Regression Example – High School and Beyond 
10:4511:00  Break 
11:0012:15  Continuation: Regression Example
· High School and Beyond (HSB) Example: Twolevel model o Within school regressions o Comparing regressions across schools o Conditional model example and interpretation o The logic of 2 level models the multilevel and the combined form equations 
12:15 – 1:30  Lunch 
1:30 3:00  Using R – Analysis walkthrough
· Brief intro to R · Data Structures for MLM · Manipulating data using R o Aggregating variables o Creating new variables (e.g., centering) · Getting started in R for Multilevel Modeling 
3:154:45  Building twolevel models
· Model 1 Oneway random effects ANOVA (totally unconditional model) o ICC o Interpretation of fixed and random effects · Model 2 Random coefficients model (unconditional model) o Change in level1 variance o Variance and covariance components o Interpretation of fixed and random effects · Model 3 Intercepts and slopes as outcomes (conditional model) o Reduction in level2 variance o Residual variance and covariance components o Interpretation of fixed and random effects 
4:455:00  Recap and Q&A 
Day 2: Tuesday, June 12
8:30 – 9:00  Continental Breakfast, 319 Gentry 
9:00 – 9:15  Q & A from Day 1 
9:15 – 10:45  Model Assessment Issues

10:45 – 11:00  Break 
11:0012:15  Centering

12:15 – 1:30  Lunch (on your own)

1:30 – 3:30  Longitudinal Models in R

3:30 3:45  Break 
3:45 – 4:45  Structured Lab I – Organizational Data

4:45 – 5:00  Questions and Answers – Lab review 
Day 3: Wednesday, June 13
8:30 – 9:00  Continental Breakfast 
9:00 – 9:15  Q & A from Day 2 
9:15 – 10:30  Longitudinal Growth Models in R: PIAT reading examples
Time structured versus Time unstructured data Running and interpreting a two level model with level 2 covariates 
10:30 – 10:45  Break 
10:45 – 12:00  § Intro to time varying covariates
NYS Example 
12:00 – 1:15  Lunch (on your own)

1:15 – 2:15  · Interaction between time and time varying covariates
o Unemployment example 
2:15 – 3:30  · Modeling discontinuity change in slope; change in intercept
o Wages example 
3:30 – 3:45  Break 
3:45 – 4:45  Structured Lab II – Longitudinal data

4:45 – 5:00  Recap and Q&A 
Day 4: Thursday, June 14
8:30 – 9:00  Continental Breakfast 
9:00 – 9:15  Q & A from Day 3 
9:15 – 10:30  Piecewise and Polynomial Models for NonLinear Growth
· Fit and interpretation o NYS as a nonlinear model (Piecewise) 
10:30 – 10:45  Break 
10:45 – 12:00  Polynomial Models for NonLinear Growth
o NYS as a nonlinear model (Cubic) Comparison to piecewise model 
12:00 – 1:15  Lunch (on your own)

1:15 – 2:45  Checking assumptions: Consideration of more complex error variancecovariance structures; Heterogeneous Variances 
2:453:00  Break 
3:004:00  Graphing 
4:005:30  Open lab time and Individual Consultations 
Day 5: Friday, June 15
8:30 – 9:00  Continental Breakfast 
9:00 – 10:15  Graphing your results (and presenting your results) 
10:1510:30  Break and Evaluations 
10:4512:00  Power Analysis and Sample Size 
12:00  Closing Luncheon – Gentry 144 
Register for the Multilevel Modeling workshop here.