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Jeffrey R. Harring
Associate Professor
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Short Professional Bio |
Dr. Harring is Associate Professor of Measurement, Statistics, and Evaluation (EDMS) in the Department of Human Development and Quantitative Methodology at the University of Maryland. Prior to joining the the EDMS faculty in the fall of 2006, Dr. Harring received a M.S. degree in Statistics in 2004, and completed his Ph.D. in the Quantitative Methods Program within Educational Psychology in 2005--both degrees coming from the University of Minnesota. Before that, Dr. Harring taught high school mathematics for 12 years.
Dr. Harring teaches quantitative methods courses making up the EDMS graduate-level statistics sequence: EDMS 645 - Quantitative Methods I, EDMS 646 - Quantitative Methods II, and EDMS 651 - Applied Multiple Regression Analysis. Corresponding more to his own research interests, Dr. Harring has also taught advanced graduate seminars on longitudinal data analysis (EDMS 769L), statistical computing and Monte Carlo simulation (EDMS 779), and finite mixture models in measurement and statistics (EDMS 769M).
Dr. Harring's research interests focus on applications of (i) statistical models for repeated measures data, (ii) nonlinear structural equation models, and (iii) statistical computing. In 2011, Dr. Harring co-authored a book with colleagues Andrew Zieffler and Jeff Long entitled, Comparing groups: Randomization and bootstrap methods using R, which was published by Wiley. More recently, with his colleague Greg Hancock, Dr. Harring co-edited a volume entitled, Advances in longitudinal methods in the social and behavioral sciences, which was published by IAP in the summer of 2012.
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Courses |
- EDMS 645: Quantitative Research Methods I.
You can access course materials from the class webpage 645.
- EDMS 646: Quantitative Research Methods II.
I last taught this course in Summer 2009. Click here to see a syllabus. Note that topics for the course could change.
- EDMS 651: Applied Multiple Regression Analysis.
You can access course materials from the class webpage 651.
- EDMS 769L: Statistical Analysis of Longitudinal Data.
I last taught this course in Spring 2012. Click here to see a syllabus. Note that topics for the course could change.
- EDMS 769M: Finite Mixture Models in Statistics and Measurement.
I last taught this course in Fall 2011. Click here to see a syllabus. Note that topics for the course could change.
- EDMS 779: Mathematical Foundations and Simulation Techniques.
I last taught this course in Fall 2012. Click here to see a syllabus. Note that topics for the course could change.
Disclaimer: Class notes are not guaranteed to be error-free. If you find what you think is an error, please notify me.
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Scholarly Work (in chornological order) |
2013
Kang, Y., & Harring, J. R. (under review). Reexamining the impact of non-normality in two-group comparison procedures. Journal of Experimental Education.
Blozis, S. A., & Harring, J. R. (under review). Understanding individual-level change through the basis functions of a latent curve model. Journal of Educational and Behavioral Statistics.
Harring, J. R., & Blozis, S. A. (under review). Fitting Correlated Residual Error Structures in Nonlinear Mixed-Effects Models Using SAS PROC NLMIXED. Behavioral Research Methods.
Harring, J. R. (under review). A piecewise model for latent variables. British Journal of Statistical and Mathematical Psychology.
Kohli, N., Harring, J. R., & Hancock, G. R. (under review). Estimating unknown knots in piecewise linear-linear latent growth mixture models. Educational and Psychological Measurement.
Hsu, J.-C., Harring, J. R., & Hancock, G. R. (under review). Finite mixtures of latent interaction models.
Silverman, R. D., Proctor, C. P., Harring, J. R., Meyer, A., & Montecillo, C. (under review). The contribution of linguistic awareness to reading comprehension for English monolingual and Spanish-English bilingual children in second through fifth grade.
Silverman, R. D., Proctor, C. P., Harring, J. R., Meyer, A., Doyle, B., & Mitchell, M. (under review). Relationships among instructional practices and vocabulary and comprehension outcomes with English-only (EO) and English-learner (EL) students in grades 3-5.
Kohli, N., & Harring, J. R. (in press). Modeling growth in latent variables using a piecewise function. Multivariate Behavioral Research.
Leider, C.M., Proctor, C.P., Silverman, R.D., & Harring, J. R. (in press). 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.
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). Greenwood, CT: Information Age Publishing, Inc.
2012
Cudeck, R., & Harring, J. R. (2012). Estimating the correlation between two variables when individuals are measured repeatedly. In M. C. Edwards & R. C. MacCallum (Eds.), Current topics in the theory and application of latent variable models (pp. 11-23). New York, NY: Routledge/Taylor & Francis.Harring, J. R., & Hancock, G. R. (Eds.) (2012). Advances in longitudinal methods in the social and behavioral sciences. Charlotte, NC: Information Age Publishing, Inc.
Harring, J. R. (2012). Finite mixtures of nonlinear mixed effects models. In J. R. Harring & G. R. Hancock (Eds.), Advances in longitudinal methods in the social and behavioral sciences (pp. 159-192). Charlotte, NC: Information Age Publishing, Inc.
Dardick, W., & Harring, J. R. (2012). Automated path tracing for general linear models. Mutliple Linear Regression Viewpoints, 38, 38-50. Accompanying SAS Program for APT paper.
Mislevy, J. L., Rupp, A. A., & Harring, J. R. (2012). Detecting local item dependence in polytomous adaptive data. Journal of Educational Measurement, 49, 127-147.
Harring, J. R., Kohli, N., Silverman, R., & Speece, D. L. (2012). Fitting a second-order conditionally linear mixed effects model as an SEM in Mplus. Structural Equation Modeling: A Multidisciplinary Journal, 19, 118-136.
Harring, J. R., Weiss, B. A., & Hsu, J.-C. (2012). A comparison of methods for estimating quadratic effects in structural equation models. Psychological Methods, 17, 193-214.
Silverman R., Speece, D. L., Harring, J. R., & Ritchey, K. (2012). Fluency has a role in the Simple View of Reading. Scientific Studies of Reading. doi: 10.1080/10888438.2011.618153
Proctor, C.P., Silverman, R. D., Harring, J. R., & Montecillo, C. (2012). The role of vocabulary depth in predicting reading comprehension among English monolingual and Spanish-English bilingual children in elementary school. Reading and Writing, 25, 1635 – 1644.
2011
Zieffler, A. S., Harring, J. R., & Long, J. D. (2011). Comparing groups: Randomization and bootstrap methods using R. New York: Wiley.
Liu, M., Hancock, G. R., & Harring, J. R. (2011). Using finite mixture modeling to deal with systematic measurement error: A case study. Journal of Modern Applied Statistical Methods, 10, 249-261.
Harring, J. R., & Wasko, J. A. (2011). Probabilistic inferences for the sample Pearson product moment correlation in the social sciences.Journal of Modern Applied Statistical Methods, 10, 4379-493.
King, B. D., Kagerer, F., Harring, J. R., Contreras-Vidal, J., & Clark, J. (2011). Multisensory adaptation of spatial-to-motor transformations in children with Developmental Coordination Disorder. Experimental Brain Research, 212, 257-265. doi: 10.1007/s00221-011-2722-z
Proctor, P., Silverman, R. D., Harring, J. R., & Montecillo, C. (2011). The role of vocabulary depth in predicting reading comprehension among English monolingual and Spanish-English bilingual children in elementary school. Reading and Writing: An Interdisciplinary Journal. doi: 10.1007/s11145-011-9336-5
King B. R., Harring J. R., Oliveira, M. A., & Clark J. E. (2011). Statistically characterizing intra- and inter-individual variability in children with developmental coordination disorder. Research in Developmental Disabilities. doi: 10.1016/ j.ridd.2010.12.043
2010
Cudeck, R., & Harring, J. R. (2010). Developing a random coefficient model for nonlinear repeated measures data. In S.-M. Chow, E. Ferrer, & F. Hsieh (Eds.), Statistical methods for modeling human dynamics: An interdisciplinary dialogue (pp. 289-318). New York: Routledge.
Harring, J. R. (2010). Concomitant variables. In N. J. Salkind (Ed.), Encyclopedia of Research Design. New York: Sage.
2009
Choi, J., Harring, J. R., & Hancock, G. R. (2009). Latent growth modeling for logistic response functions. Multivariate Behavioral Research,44, 620-645.
Harring, J. R. (2009). A nonlinear mixed effects model for latent variables. Journal of Educational and Behavioral Statistics,34, 293-318.
Cudeck, R., Harring, J. R., & du Toit, S. H. C. (2009). Marginal maximum likelihood estimation of a latent variable model with interaction. Journal of Educational and Behavioral Statistics,34, 131-144.
2008
Blozis, S. A., Harring, J. R., & Mels, G. (2008). Using LISREL to fit nonlinear latent curve models. Structural Equation Modeling. A Multidisciplinary Journal, 15, 346-369.
2007
Cudeck, R., & Harring, J. R. (2007). The analysis of nonlinear patterns of change with random coefficient models. Annual Review of Psychology, 58, 615-637.
Long, J. D., Harring, J. R., Brekke, J. S., Test, M. A., & Greenberg, J. (2007). Longitudinal construct validity of brief symptom inventory subscales in schizophrenia. Psychological Assessment, 19, 298-308.
Blozis, S. A., Conger, K. J., & Harring, J. R. (2007). Nonlinear latent curve models for longitudinal data. International Journal of Behavioral Development: Special Issue on Longitudinal Modeling of Developmental Processes, 31, 340-346.
2006
Harring, J. R., Cudeck, R., & du Toit, S. H. C. (2006). Fitting partially nonlinear random coefficient models as SEMs.Multivariate Behavioral Research, 41, 579-596.
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Selected Presentations |
Return to topKang, Y., & Harring, J. R. (2012, May). Investigating the Impact of Non-Normality, Effect Size, and Sample Size on Two-Group Comparison Procedures: An Empirical Study. Presented at the annual meeting of the American Educational Research Association (AERA), SIG: Educational Statisticians, Vancouver, BC. (Student Paper Award Winner)
Hancock, G. H., & Harring, J. R. (2011, May). Using Phantom Variables in Structural Equation Modeling to Assess Model Sensitivity to External Misspecification. Presented at the Modern Modeling Methods Conference, University of Connecticut.
Kohli, N., & Harring, J. R. (2011, April). Modeling growth in latent variables using a piecewise function. Presented at the annual meeting of the American Educational Research Association (AERA), SIG: Educational Statisticians, New Orleans, LA. (Student Paper Award Winner)
Harring, J. R. (2011, April). A piecewise regression model for latent variables. Presented at the annual meeting of the American Educational Research Association (AERA), SIG: Structural Equation Modeling, New Orleans, LA.
Harring, J. R., & Liu, J. (2011, April). A comparison of estimation methods for nonlinear mixed effects models under model misspecification and data sparseness: A simulation study. Presented at the annual meeting of the American Educational Research Association (AERA), Division D – Section 2: Statistical Theory and Methods, New Orleans, LA.
Cudeck, R., & Harring, J. R. (2010, September). On computing the correlation of repeated measures data. Presented at Current Topics in the Theory and Application of Latent Variable Models: A Conference Honoring the Scientific Contributions of Michael W. Browne, The Ohio State University, Columbus, OH.
Harring, J. R. (2010, June). Finite Mixtures of Nonlinear Mixed Effects Models. Presented at the Advances in Longitudinal Methods in the Social and Behavioral Sciences Conference, University of Maryland, College Park, MD.
Harring, J. R., & Choi, J. (2010, May). Nonlinear latent growth modeling using Markov chain Monte Carlo estimation. Presented at the annual meeting of the American Educational Research Association, Denver (AERA), SIG: Structural Equation Modeling, CO.
Harring, J. R., Weiss, B. A., & Hsu, J. C. (2010, May). A comparison of methods for estimating quadratic effects in nonlinear structural equation models. Presented at the annual meeting of the American Educational Research Association (AERA), SIG: Structural Equation Modeling, Denver, CO.
Harring, J. R. (2009, June). Modern methods for the study of longitudinal change. Presentation at the Developmental Coordination Disorder International Conference, Baltimore, MD.
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