Quantitative Methodology: Measurement and Statistics, Ph.D.
Doctor of Philosophy
Program Overview
The Quantitative Methodology: Measurement and Statistics, Ph.D. program is tailored for aspiring scholars seeking advanced training in research methods and statistical analysis. With a focus on generating and disseminating new knowledge in quantitative methodology, this research-oriented program prepares you for careers in any industry. You will learn to design and conduct research studies, analyze data using sophisticated statistical techniques, and interpret and present research findings effectively.
If you possess strong analytical ability and a passion for research, this program might be the right fit for you.
Key Features
- Research Focus: Engage in scholarly research activities aimed at advancing the field of quantitative methodology.
- Teaching Preparation: Gain the necessary skills to teach courses at the university level in applied measurement, statistics, and evaluation.
- Customizable Curriculum: Tailor your course of study with electives selected in consultation with your advisor to align with your research interests and career goals.
- Interdisciplinary Opportunities: Collaborate with faculty and students from diverse academic backgrounds to address complex research questions.
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Best Education School by U.S. News & World Report
Learning Outcomes
Learning Outcomes
- Demonstrate proficiency in advanced quantitative research methods and statistical analysis.
- Conduct original research contributing to the body of knowledge in quantitative methodology.
- Effectively communicate research findings through scholarly publications and presentations.
- Provide leadership in the design, implementation, and evaluation of research studies in various settings.
How to Apply
How to Apply
Information on admissions and application to this program can be found on the University Graduate Admissions website.
You are required to submit all required documents before submitting the application.
Program Specific Requirements
- Letters of Recommendation (3)
- Graduate Record Examination (GRE)
- CV/Resume
- Writing Sample
“After two years in QMMS, I realized no other programs in the field can better prepare me for my career goals than this program. So I only applied to this one program for my Ph.D. The program really stands out in our field with its rigorous research training, well-structured curriculum, and diverse expertise and research interests among the faculty. It offers me great opportunities to engage in various research projects and explore my own interests.”
Requirements
Program Requirements
Courses in this program are carefully selected from offerings of Quantitative Methodology: Measurement and Statistics program and other departments at the University. Your specific program of study will be structured to take into account your background and future aims.
Program of Study
- EDMS 623 Applied Measurement: Issues and Practices (3)
- EDMS 626 Instrumentation (3)
- EDMS 646 General Linear Models I (3)
- EDMS 647 Causal Inference and Evaluation Methods (3)
- EDMS 651 General Linear Models II (3)
- EDMS 655 Introduction to Multilevel Modeling (3)
- EDMS 657 Exploratory Latent and Composite Variable Methods (3)
- EDMS 722 Structural Modeling (3)
- EDMS 724 Modern Measurement Theory (3)
- EDMS 779 Mathematical Foundations and Simulation Techniques (3)
- EDMS 787 Bayesian Inference and Analysis (3)
- EDMS 899 Doctoral Dissertation Research (12)
You must select at least 21 credits of elective courses in consultation with your advisor. A minimum of 30 credit hours (including EDMS 899) must be taken following admission.
In addition to courses, you must complete a doctoral preliminary examination and a doctoral comprehensive examination and are expected to participate in research and publication. A faculty advisor may require courses beyond those specified here.
The many and varied professional interests of faculty members provide opportunities for presentations of research reports by students as well as faculty. Recent presentations by students have dealt with a variety of original research topics, in such areas as applied statistics, modeling of traits, test construction, test evaluation, and survey research.
Faculty
Faculty
Our faculty are chosen for their expertise and dedication; they provide exceptional guidance and support to foster your academic and professional success.
Gregory R. Hancock, Professor and Program Director
UM Distinguished Scholar-Teacher
1230D Benjamin Building
(301) 405-3621 | ghancock@umd.edu
Jeffrey Harring, Professor
1230E Benjamin Building
(301) 405-3630 | harring@umd.edu
Hong Jiao, Professor
1230C Benjamin Building
(301) 405-3627 | hjiao@umd.edu
Yang Liu, Associate Professor
1230B Benjamin Building
(301) 314-1126 | yliu87@umd.edu
Laura Stapleton, Professor and HDQM Chair
1230A Benjamin Building
(301) 405-1933 | lstaplet@umd.edu
Peter Steiner, Professor
1233 Benjamin Building
(301) 405-6396 | psteiner@umd.edu
Tracy Sweet, Associate Professor
1229 Benjamin Building
(301) 405-3623 | tsweet@umd.edu
Ji Seung Yang, Professor and Director of Graduate Studies
1225 Benjamin Building
(301) 405-6073 | jsyang@umd.edu
Contact
Contact
For more information, please contact:
Dr. Gregory R. Hancock
Director of QMMS
ghancock@umd.edu
For advising questions, please contact:
Dr. Ji Seung Yang
Director of Graduate Studies
jsyang@umd.edu