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Welcome from the Program Director
EDMS Students and Events
Upcoming Events

Chair > Welcome to the programs in Measurement, Statistics and Evaluation in the Department of Human Development and Quantitative methodology. We offer some of the nation's premiere graduate training in psychometric and statistical methods. Through our Ph.D, M.A., and Certificate programs, EDMS students become trained in modern analytical methods to prepare them for careers in academia and applied research. Our faculty are engaged in world-class research at the frontiers of our field, creating opportunities for our students to be mentored in all phases of the research process. I am honored to serve a program with such remarkable faculty, students, and alumni, and I encourage you learn more about what makes us so special.                                               -- Gregory R. Hancock

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> MSMS presentation: The Maryland Longitudinal Data System Synthetic Data Project. Monday, April 10, 2017, 10:30-11:30, 0306 Benjamin. Click here for more details.

> Introduction to Bayesian Statistical Modeling, Dr. Roy Levy, June 7-9, 2017. Click here for more details.

Some Recent Publications by EDMS Faculty and Students
News Items

> Sweet, T. M. (in press). About social network models used in education research. In A. Von Davier, P.C. Kyllonen, & M. Zhu (Eds.), Innovative assessment of collaboration. New York, NY: Springer.
> Sweet, T. M., & Zheng, Q. (in press). Multilevel social network models: incorporating network-level covariates into hierarchical latent space models. In J. Harring, L. Stapleton, & S. Beretvas (Eds.), Advances in multilevel modeling for educational research: Addressing practical issues found in real-world applications. Charlotte, NC: Information Age Publishing.
> McNeish, D., & Harring, J. R. (in press). Clustered data with small sample sizes: Comparing the performance of model-based and design-based approaches. Communication in Statistics: Simulation and Computation.
> McNeish, D. M., & Stapleton, L.M. (in press). The effect of small sample size on two level model estimates: A review and illustration. Educational Psychology Review
> Yang, J. S., & Cai, L. (in press). Estimation of contextual effects through nonlinear multilevel latent variable modeling with a Metropolis-Hastings Robbins-Monro algorithm. Journal of Educational and Behavioral Statistics.
> Jiao, H., & Lissitz, R. W. (in press). Direct modeling of student growth with multilevel and mixture extensions. In R. W. Lissitz & H. Jiao (Eds.), Value added modeling and growth modeling with particular application to teacher and school effectiveness. Charlotte, NC: Information Age Publishing, Inc.
> Stapleton, L. M., Pituch, K. A., & Dion, E. (in press). Standardized effect size measures for mediation analysis in cluster-randomized trials. Journal of Experimental Education. doi: 10.1080/00220973.2014.919569
> Wolfe, E. W., Jiao, H., & Song, T. (in press). A family of rater accuracy models. Journal of Applied Measurement.
> Kohli, N., Harring, J. R., & Hancock, G. R. (in press). Estimating unknown knots in piecewise linear-linear latent growth mixture models. Educational and Psychological Measurement.
> Hancock, G. R., & McNeish, D. M. (in press). More powerful tests of simple interaction contrasts in the two-way factorial design. Journal of Experimental Education.
> Kang, Y., McNeish, D. M., & Hancock, G. R. (in press). The role of measurement quality on practical guidelines for assessing measurement and structural invariance. Educational and Psychological Measurement.
> Blozis, S. A., & Harring, J. R. (in press). Understanding individual-level change through the basis functions of a latent curve model. Sociological Research Methods.
> Harring, J. R., & Stapleton, L. M., & Beretvas, S. N. (Eds.) (in press). Advances in multilevel modeling for educational research: Addressing practical issues found in real-world applications. Charlotte, NC: Information Age Publishing, Inc.
> Harring, J. R., Beretvas, S. N., & Israni, A. (in press). A model for cross-classified nested repeated measures data. In J. R. Harring, L. M. Stapleton, & S. N. Beretvas (Eds.), Advances in multilevel modeling for educational research: Addressing practical issues found in real-world applications. Charlotte, NC: Information Age Publishing, Inc.
> Stapleton, L. M.Harring, J. R., Lee, D. (in press). Sampling weight considerations for multilevel modeling of panel data. In J. R. Harring, L. M. Stapleton, & S. N. Beretvas (Eds.), Advances in multilevel modeling for educational research: Addressing practical issues found in real-world applications. Charlotte, NC: Information Age Publishing, Inc.
> Harring, J. R., & Houser, A. (in press). Longitudinal models for discrete and continuous variables: Modeling developmental processes. In A. A. Rupp, & J. Leighton (Eds.), Submitted to Handbook of Cognition and Assessment.
> Kohli, N., Harring, J. R., Zopluoglu, C. (2015). Estimation of the finite mixture of nonlinear random coefficient models. Psychometrika. doi: 10.1007/s11336-015-9462-0
> Leite, W. L., Jimenez, F., Kaya, Y., Stapleton, L. M., MacInnes, J. W., & Sandbach, R. (in press). An evaluation of weighting methods based on propensity scores to reduce selection bias in multilevel observational studies. Multivariate Behavioral Research.

 

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> Congratulations to Dr. Laura Stapleton for being named a University of Maryland Graduate Faculty Mentor of the Year.
 
> Congratulations to EDMS student Kaiwen Man for receiving an ETS Gulliksen fellowship.

 

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