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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 department 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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> Introduction to Bayesian Statistical Modeling short course: July 22-24, 2014. Roy Levy. Click here for info.

> Applied Data Analysis Using R short course: August 13-15, 2014. Jeffrey Harring. Click here for info.

Recent Publications by EDMS Faculty and Students
News Items

> Sweet, T. M., Thomas, A. C., & Junker, B. W. (2013). Hierarchical social network models for education interventions. Journal of Educational and Behavioral Statistics, 38, 295-318. doi: 10.3102/1076998612458702

> Sweet, T. M., Thomas, A. C., & Junker, B. W. (in press). Hierarchical mixed membership stochastic blockmodels for multiple networks and experimental interventions. Handbook of Mixed Membership Models. New York: Chapman & Hall/CRC.

> Stapleton, L. M. (2013). Using multilevel structural equation modeling techniques with complex sample data. In G. R. Hancock & R. O. Mueller (Eds), Structural equation modeling: A second course (2nd ed.) (pp. 521-562). Charlotte, NC: Information Age Publishing.

> 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.

> Kohli, N., & Harring, J. R. (2013). Modeling growth in latent variables using a piecewise function. Multivariate Behavioral Research, 48, 370-397.

> Hancock, G. R., Harring, J. R., & Lawrence, F. R. (2013). Using latent growth models to evaluate longitudinal change. In G. R. Hancock & R. O. Mueller (Eds.), Structural equation modeling: A second course (2nd ed.). Charlotte, NC: Information Age Publishing, Inc.

> Leider, C. M., Proctor, C. P., & Silverman, R. D., & Harring, J. R. (2013). Examining the role of vocabulary depth, cross-linguistic transfer, and types of reading measures on the reading comprehension of Latino bilinguals in elementary school. Reading and Writing: An Interdisciplinary Journal. doi: 10.1007/s11145-013-9427-6.

> Silverman R. D., Speece, D. L., Harring, J. R., & Ritchey, K. (2013). Fluency has a role in the Simple View of Reading. Scientific Studies of Reading, 17, 108-133. doi: 10.1080/10888438.2011.618153.

> Jiao, H., Wang, S., & He, W. (2013). Estimation methods for one-parameter testlet models. Journal of Educational Measurement, 50,186-203.

> Jiao, H., & Chen, Y.-F. (2014). Differential item and testlet functioning. In A. Kunnan (Ed.), The companion to language assessments (pp.1282-1300). New York: John Wiley & Sons, Inc.

> Tao, J., Xu, B., Shi, N., & Jiao, H. (2013). Refining the two-parameter testlet response model by introducing testlet discrimination parameters. Japanese Psychological Research, 55, 284-291.

> Wang, S., McCall, M., Jiao, H., & Harris, G. (2013). Construct validity and measurement invariance of computerized adaptive testing: application to Measures of Academic Progress (MAP) using confirmatory factor analysis. Journal of Educational and Developmental Psychology, 3, 88-100.

> Lissitz, R. W. (Ed.)(2013). Informing the practice of teaching using formative and interim assessment: A systems approach. Charlotte, NC: Information Age Publishing, Inc.

> Hancock, G. R., Mao, X., & Kher, H. (2013). On latent growth models for composites and their constituents. Multivariate Behavioral Research, 48, 619-638.

> Hancock, G. R., Harring, J. R., & Lawrence, F. R. (2013). Using latent growth models to evaluate longitudinal change. In G. R. Hancock & R. O. Mueller (Eds.), Structural equation modeling: A second course (2nd ed.) (pp. 307-340). Charlotte, NC: Information Age Publishing, Inc.

> Hancock, G. R., & Mueller, R. O. (Eds.) (2013). Structural equation modeling: A second course (2nd ed.). Charlotte, NC: Information Age Publishing, Inc.

 

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> Congratulations to the following students on their upcoming summer internships: Dan McNeish (ACT), Daniel Lee (KICE), Yoonjeong Kang (AIR), Tiago Calico (ETS), Huili Liu (ETS), and Ming Li (CAL).

> Congratulations to Dan McNeish for receiving a Graduate School All-S.T.A.R. Fellowship Award.

> Congratulations to Xiulin Mao for receiving a Graduate School Summer Research Award.

> Congratulations to Rosalyn Bryant for receiving the Distinguished Graduate Teaching Assistant Award.

> Congratulations to Dr. Hong Jiao for receiving the 2014 Bradley Hanson Award for significant contributions to the field of educational
measurement, by the National Council on Measurement in Education.

> Congratulations to Dr. Gregory R. Hancock for being named a University of Maryland Distinguished Scholar-Teacher.

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