The Center for Integrated Latent Variable Research (CILVR)

presents

     MODERN LONGITUDINAL DATA ANALYSIS:

LINEAR AND NONLINEAR MIXED EFFECTS MODELS USING R

                    FEBRUARY 20-22, 2019

taught by

Jeffrey R. Harring, University of Maryland

 

SHORT COURSE DESCRIPTION

This three-day short course is intended as both a theoretical and practical introduction to modern statistical techniques for longitudinal data analysis as it pertains to methods regularly used in educational, behavioral, and social science research. An understanding of modern longitudinal data analytic methods will be developed by relating it to participants’ existing knowledge of traditional statistical methods, particularly multiple linear regression. A participant’s experience in this workshop will be enhanced by additional prior coursework or knowledge of advanced statistical techniques such as multilevel modeling. 

An outline of topics covered during the three-day short course follow sound principles of any data analytic endeavor. The course begins with discussion of longitudinal designs, data management, and exploratory data analysis. Linear mixed-effects models focusing on specifying a model for individuals, means, variances, and covariances will be presented. Maximum likelihood and Bayesian estimation approaches will be discussed as a precursor to drawing inferences through the hypothesis testing paradigm. On the third day, nonlinear longitudinal models will be presented and many extensions to basic models will be discussed.

Examples used in this short course draw primarily from social and behavioral science research, including the fields of education and psychology. Datasets will be made available to participants as well as R scripts to run the examples and annotated output. Throughout the course, participants will be able to practice exercises using R statistical software and because it is freely available, participants are encouraged to bring their own laptops with R pre-installed to perform these exercises. Participants will be instructed on how to download R prior to the course.

TARGET AUDIENCE

Graduate students, emerging researchers, continuing researchers

REQUISITE KNOWLEDGE

Participants should have a foundational knowledge up through multiple regression. Prior experience with multilevel or mixed-effects modeling is a plus, but not required.

Although prior experience with R software is not required, a basic knowledge of R will enhance the participant's experience.

SOFTWARE

Models and hands-on exercises for this workshop will be done using R statistical software. Participants are welcome to bring the software loaded on their own computer, although this is not required.

DATES AND TIMES

Modern Longitudinal Data Analysis: Linear and Nonlinear Mixed-Effects Models Using R

February 20-22, 2019: 9:00-4:30 (check-in 8:30am)

Continental Breakfast*: 8:30 AM - 9:00 AM
Morning Session: 9:00 AM - 12:15 PM
Lunch (on your own): 12:15 PM - 1:15 PM
Afternoon Session: 1:15 PM - 4:30 PM

* Participants who have special dietary needs or preferences are welcome to bring their own food as well.

LOCATION

Thurgood Marshall Room, Room 2113
Adele H. Stamp Student Union
University of Maryland
College Park, MD 20742

Link to campus maps

COURSE FEES
(seats limited)

$895 for all three days; $595 for full-time students; (free for registered HDQM Department faculty and students, although you must register; admission will depend on if space is available).

ON-LINE OPTION: $295 for all three days. See below for details.

UNDERREPRESENTED GROUPS

Support for students from Underrepresented Groups to attend methodological workshops (from the Society of Multivariate Experimental Psychology):

https://www.smep.org/resources/underrepresented-fellowships

ON-LINE OPTION

Format: On-line participants will receive a personalized login code to use on their own computer to access a reliable live-stream of the workshop, showing the instructor as well as the handouts displayed on screen to on-site participants.

Materials: On-line participants will receive electronic copies of the workshop materials that on-site participants receive, as well as any other relevant materials or information.

Timing/access: On-line participants may choose to watch the stream synchronously, or may elect to watch a recording of the workshop asynchronously, or both. With DVR-like capabilities, and access to the recordings for one-week after the end of the workshop, this format allows on-line participants to choose when they engage. This is especially useful for on-line participants in different time zones, or anywhere in the world, who may choose to watch at some later time than (but within a week of) the actual workshop time. (Asynchronous participation does not include real-time chat with other on-line participants, although a visual record of prior chats will be viewable).

Technical support: Participants are assumed to be able to secure a reliable computer, internet browser, and Wi-Fi connection. Challenges at the user end must be resolved by the user. Fortunately, because the workshop is recorded, users experiencing technical challenges can still “catch up” by watching the recordings to which they have access.

Content support: Content support for on-line participants is limited to real-time chat with the on-line participant community and any quantitative methodology doctoral students who might also be participating. There is no mechanism for on-line participants to submit individual questions to the instructor.

Hands-on activities: On-line participants may choose to try any hands-on activities being done by on-site participants using their own computational facilities and software; however, support for such activities is limited to the on-site participants.

Cost: See course fees above; includes access to the workshop recordings for one week total, and electronic copies of all materials.

HOW TO REGISTER

Please register using the preferred on-line registration form:
On-line short-course registration form
(Note: For those students who are not in the HDQM department please fill out the paper registration form and upload it when prompted within the on-line registration system).

For those who prefer not to use the on-line registration system, please complete and submit the following paper registration form: Longitudinal2019_PaperForm.pdf

Note that it may take up to 7-10 business days for your registration to be processed.

QUESTIONS?

Contact Ms. Yi Feng: longitudinal2019@gmail.com

NEARBY AIRPORTS

local airports

DRIVING DIRECTIONS

From Baltimore and Points North

  • Take I-95 South to Washington, D.C.'s Capital Beltway (I-495).
  • Take Exit 27 and then follow signs to Exit 25 (U.S. 1 South toward College Park).
  • Proceed approximately two miles south on U.S. Route 1.
  • Turn right into Campus Drive entrance (main gate).
  • Proceed up Campus Dr. to the "M" circle, go halfway around the circle and continue on Campus Dr (second right after entering the circle).
  • Proceed up Campus Dr. to the "M" circle, go halfway around the circle and continue on Campus Dr (second right after entering the circle) until you see Stamp Student Union on your right side.

From Virginia and Points South

  • Take I-95 North to Washington, D.C.'s Capital Beltway (I-495).
  • Continue North on I-95/I-495 toward Baltimore.
  • Take Exit 25 (U.S. 1 South toward College Park).
  • Proceed approximately two miles south on U.S. Route 1.
  • Turn right into Campus Drive entrance (main gate).
  • Proceed up Campus Dr to the "M" circle, go halfway around the circle and continue on Campus Dr (second right after entering the circle) until you see Stamp Student Union on your right side.

From Virginia and Points West

  • Take I-66 East or I-270 South to Washington, D.C.'s Capital Beltway (I-495).
  • Go East on I-495 toward Baltimore/Silver Spring.
  • Take Exit 25 (U.S. 1 South toward College Park).
  • Proceed approximately two miles south on U.S. Route 1.
  • Turn right into Campus Drive entrance (main gate).
  • Proceed up Campus Dr. to the "M" circle, go halfway around the circle and continue on Campus Dr (second right after entering the circle) until you see Stamp Student Union on your right side.

From Annapolis and Points East

  • Take U.S. 50 to Washington, D.C.'s Capital Beltway (I-495).
  • Go North on I-95/I-495 toward Baltimore.
  • Take Exit 25 (U.S. 1 South toward College Park).
  • Proceed approximately two miles south on U.S. Route 1.
  • Turn right into Campus Drive entrance (main gate).
  • Proceed up Campus Dr to the "M" circle, go halfway around the circle and continue on Campus Dr (second right after entering the circle) until you see Stamp Student Union on your right side.

From Washington, D.C. (Northwest/Southwest)

  • Take 16th St. North which becomes Georgia Ave. North at Maryland/D.C. line.
  • Go East on I-495 toward Baltimore.
  • Take Exit 25 (U.S. 1 South toward College Park).
  • Proceed approximately two miles south on U.S. Route 1.
  • Turn right into Campus Drive entrance (main gate).
  • Proceed up Campus Dr to the "M" circle, go halfway around the circle and continue on Campus Dr (second right after entering the circle) until you see Stamp Student Union on your right side.

From Washington, D.C. (Northeast/Southeast)

  • Take Rhode Island Ave. (U.S. 1 North) which becomes Baltimore Ave. North at Maryland/D.C. line.
  • Proceed through the city of College Park.
  • Turn left at Campus Drive entrance (main gate).
  • Proceed up Campus Dr to the "M" circle, go halfway around the circle and continue on Campus Dr (second right after entering the circle) until you see Stamp Student Union on your right side.

VISITOR PARKING

Participants may park at the Union Lane Garage (located between the Adele H. Stamp Student Union and Cole Field House) for a daily fee. There are numerous metered spaces on campus but the University police are diligent about ticketing cars at expired meters as well as cars without appropriate stickers in reserved parking lots.

More information about parking on University of Maryland Campus can be found at the web site: http://www.cvs.umd.edu/visitors/parking.html

METRO (SUBWAY)

The Campus is conveniently located approximately 1 mile from the College Park-University of Maryland Metro Station. The stop is on the green line of the D.C. Metro System. The University of Maryland Shuttle Bus runs from the College Park Metro stop on a twenty-minute schedule through the Campus. Or, a brisk twenty minute walk up a moderate hill through the Campus will bring you to all locations.

D.C. Metro Map: https://www.wmata.com/schedules/maps/

ACCOMMODATIONS

Participants are responsible for arranging their own accommodations. For out-of-town guests, there are several sources of accommodations in the immediate area. Information about hotel pricing and reservations can be found at the web site: http://www.cvs.umd.edu/visitors/offcampus.htmlNote that participants will need to make their own arrangements for transportation to and from campus.

[Note that there is a hotel located on the edge of the University of Maryland campus: The Marriott Inn & Conference Center, University of Maryland University College. For more information about this hotel, visit: http://www.marriott.com/hotels/travel/wasum-college-park-marriott-hotel-and-conference-center/

ABOUT THE INSTRUCTOR

Jeffrey R. Harring is Professor of Measurement, Statistics and Evaluation in the Department of Human Development and Quantitative Methodology at the University of Maryland, where he teaches coursework in longitudinal modeling, finite mixture modeling, and simulation techniques. His research interests include statistical models of repeated measures data and his work has appeared in such journals as Structural Equation Modeling: A Multidisciplinary Journal, Psychological Methods, Multivariate Behavioral Research, Journal of Educational Measurement, Psychometrika, and Journal of Educational and Behavioral Statistics. Additionally, Dr. Harring co-authored a book entitled, Comparing Groups: Randomization and Bootstrap Methods Using R, which was published in 2011, and published co-edited volumes, Advances in Longitudinal Methods in the Social and Behavioral Sciences with Gregory R. Hancock in 2012 and Advances in Multilevel Modeling for Educational Research with Laura M. Stapleton and S. Natasha Beretvas in 2016. He is a past program chair of Division D, Section 2: Statistical Theory and Methods of the American Educational Research Association and the Structural Equation Modeling Special Interest Group. Dr. Harring holds M.S. and Ph.D. degrees from the University of Minnesota. He may be reached at harring@umd.edu