Dear MLM SIG Members,

My name is Hsien-Yuan Hsu (University of Mississippi), and it is my pleasure to serve as chair of the MLM SIG for the 2016-2017 term.  I would like to give very special thanks to the former chair, Qi Chen (University of North Texas), who has devoted much time and energy to coordinating successful MLM SIG sessions and the Quantitative SIGs Joint Social in Washington, D.C. this year.  As you are well aware, the 2017 AERA Annual Conference will be held April 27 – May 1 in San Antonio, Texas.  I sincerely invite all of you to “replicate” this year’s successful experience in the coming year by (1) volunteering as proposal reviewers, and (2) submitting your research proposals to the MLM SIG.

How to volunteer as a proposal reviewer?  The deadline for signing up as a volunteer peer reviewer is May 11, 2016.  Please visit the AERA website for detailed information:

http://www.aera.net/EventsMeetings/2017AnnualMeetingCallforVolunteerReviewers/tabid/16234/Default.aspx

How to submit your proposals to the MLM SIG?  The MLM SIG aims at promoting the development and use of Multilevel Modeling techniques; therefore, we welcome any research paper using the MLM analytical method, including manuscripts in methodological and applied areas.  The submission system is NOT open now but the deadline for submissions is usually around the LAST week of July. 

We solicit proposals on a range on topics related to MLM:

1.     All types of multilevel models (e.g., ANOVAs, multilevel regression (HLM), Multilevel SEM, IRT, factor analysis, growth, mixture, and cross-classified).

2.     Multilevel optimal design (e.g., cluster randomized designs, statistical power, sample size, effect size, and sampling weights).

3.     Causal methods for observational data with multilevel models (e.g., propensity score, instrumental variable, and regression discontinuity methods).

4.     Evaluation research with multilevel models (e.g., mediation, school effectiveness, and value added modeling).

5.     Estimation strategies for multilevel models (e.g., Bayesian, ML, and WSL).

6.     Multilevel model assessment (e.g., model assumptions, outliers, missing values, and goodness of fit).

I look forward to seeing your proposals and meeting you at the annual meeting in Texas!

​

Hsien-Yuan Hsu

Assistant Professor

Department of Leadership and Counselor Education

University of Mississippi