The Center for Integrated Latent Variable Research (CILVR)

presents

     INTRODUCTION TO ITEM RESPONSE THEORY

                    MARCH 27-29, 2019

taught by

Ji Seung Yang, University of Maryland

 

SHORT COURSE DESCRIPTION

A central theme in psychological and educational measurement is the establishment of the technical criteria and appropriate use of statistical models for ensuring the reliability, fairness, and validity of the scores that are obtained via assessments and surveys. From large-scale educational assessment (e.g., the Graduate Record Examinations; GRE) to the assessment of physical, mental, and social well-being for patients (e.g., Patient Reported Outcomes Measurement Information System), the underlying principles of measurement are similar. Item Response Theory (IRT) refers to a particular set of the modern measurement theory, models, and techniques that are utilized to develop either a large-scale assessment or a survey.  

The purpose of this three-day course is to introduce IRT to participants who have not been formally exposed to it or who would like to consolidate/extend their previous knowledge by covering both theoretical and practical basics of various IRT models including their estimation, assessment of model fit, and application to real-world assessments. The course materials were developed in collaboration with Dr. Yang Liu (also at the University of Maryland) while the short course delivery will be made by Dr. Ji Seung Yang.

The course starts with a brief review of the history of IRT. Then IRT models for various item responses (e.g., dichotomous and polytomous item responses; 1, 2, 3-parameter models, graded response models, partial credit models, and nominal response models) are introduced with empirical/simulated data examples. Estimation of model parameters and related issues are discussed. Various approaches to assess model fit are addressed before moving into more applied topics that include detection of local dependence and differential item functioning. Overall this course focuses on the statistical theory underlying IRT models as well on their applications to real and simulated data sets using computer software packages.

Empirical examples and hands-on exercises for this workshop will be done using the flexMIRT software and other supplemental software packages such as R and Excel. Participants are strongly recommended to bring the package loaded on their own laptop for a more enhanced learning experience. Further instructions will be distributed and no additional software cost will be needed for this course.

After completing the workshop, participants will be able to apply appropriate unidimensional IRT models to their own empirical data set to analyze psychometric properties of test or survey items, to obtain individual scale scores, to assess model fit and assumptions, and to detect differential item functioning items using IRT models.

TOPICS
  • Introduction and Overview
  • Models for dichotomous responses (1-, 2-, and 3-PL models)
  • Maximum likelihood estimation
  • Models for ordinal responses
  • Nominal response model and variations
  • Goodness of fit assessment (suppressing technical aspects but more focus on practical aspects)
  • IRT Scoring
  • Differential item functioning
  • Sources of IRT model misfit (taste of advanced topics, non-normal density, and bifactor model)

TARGET AUDIENCE

Graduate students, faculty, research professionals who are interested in developing measures.

REQUISITE KNOWLEDGE

It is assumed that participants have knowledge of general and generalized linear models, especially logistic regression (e.g., hypothesis testing, confidence intervals, parameter interpretation, and likelihood ratio tests). Although not required, a participant’s experience in this workshop will be enhanced by additional prior coursework or experience with measurement theory (e.g., Classical Test Theory) and latent variable modeling such as factor analysis.

SOFTWARE

Empirical examples and hands-on exercises for this workshop will be done using the flexMIRT software (to which on-site participants will have temporary access) and other supplemental software packages such as R and Excel. Participants are strongly recommended to bring the R package loaded on their own laptop for a more enhanced learning experience. On-line participants may use whatever software they have access to on their own (e.g., R, flexMIRT).

DATES AND TIMES

Introduction to Item Response Theory

March 27-29, 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
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 and attend; 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: IRTRegForm2019.pdf

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

QUESTIONS?

Contact Ms. Yishan Ding: IRT19.workshop@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

Dr. Ji Seung Yang is an Assistant Professor of Measurement, Statistics, and Evaluation (EDMS) in the Department of Human Development and Quantitative Methodology at the University of Maryland. Dr. Yang has been teaching advanced quantitative graduate seminars on multidimensional/multilevel item response theory in addition to general/generalized linear models, introduction to item response theory, and issues and practices in measurement at UMD since 2013. Her research interests encompass 1) development of statistical models that incorporate measurement errors in the frameworks of Item Response Theory, Generalizability Theory, Hierarchical Linear Modeling, and Latent Variable Modeling, and 2) development of multilevel/multidimensional item response model with efficient computation. Dr. Yang has published methodological papers in prominent journals such as PsychometrikaJournal of Educational and Behavioral StatisticsPsychological Methods, Multivariate Behavioral Research, and Educational and Psychological Measurement and application papers in the Journal of Educational Psychology. Her research has been funded by federal agencies such as the Institute of Educational Sciences (IES), National Science Foundation (NSF) to develop semiparametric multilevel bifactor models and to validate an educational construct measure, Grit. She served as the Outstanding Dissertation Award Committee Chair for AERA Division D 2017-2018, and sits on the editorial boards of flagship quantitative methods journals such as Journal of Educational and Behavioral Statistics and Journal of Educational Measurement. She is also on the IES review panel for the Basic Processes (2015-2019). Before joining the EDMS faculty in the fall of 2013, Dr. Yang worked as a postdoctoral researcher at University of California - Los Angeles where she received her Ph.D. in 2012. She may be reached at jsyang@umd.edu