Please note required coursework may vary from year to year. Current students should always defer to their Program of Work for course requirements and consult with their faculty advisor / Graduate Advisor for any needed clarifications.
Quantitative Methods doctoral students are required to complete:
- EDP Foundation courses,
- QM Program courses,
- Out-of-Specialization courses, and
- Qualifying Process and Dissertation coursework.
Student coursework may vary depending on prior graduate coursework and waivers. All required courses must be completed with a grade of at least B-.
Core Goals
Goal 1: Learn to plan and execute sophisticated quantitative research studies, as well as to analyze and evaluate the research carried out by others.
Goal 2: Acquire expertise in a variety of advanced statistical and psychometric modeling techniques including innovative techniques that are on the cutting edge of the field.
Goal 3: Learn to develop research designs and analysis strategies that are tailored to and appropriate for specific quantitative research questions, based on an understanding of the relationship between the design, the measures used and the relevant data analysis techniques.
Goal 4: Develop the problem solving skills needed to serve as a quantitative research consultant.
Goal 5: Develop the statistical, mathematical, and computing skills needed to conduct methodological research and contribute new methodological knowledge to the field.
Goal 6: Acquire the deep, conceptual understanding of measurement principles and procedures necessary to develop and understand the proper use and assessment of use of measurement instruments (surveys, questionnaires, etc.) for specific educational, psychological and social science research and evaluation purposes.
Goal 7: Learn to conduct applied psychometric research and to innovate psychometric techniques.
Goal 8: Advance the field of quantitative research methodology through exemplary teaching and research, and acquire the professional skills that will support participation and leadership in national research organizations.
Application Requirements
A master’s degree in Quantitative Methods or a related field such as Statistics or Quantitative Psychology is required.
EDP Foundation Courses (23 credit hours)
The Educational Psychology Foundation courses represent foundational knowledge in educational psychology, and reflect basic knowledge in the breadth of scientific psychology, its history of thought and development, research methods, and applications. Foundation courses must be completed prior to the Qualifying Process.
Methods Foundation (17 hours)
- Prerequisite Course: EDP 380C.2 Fundamental Statistics: prerequisite for all Methods courses.
- EDP 480C.6 Statistical Analysis for Experimental Data
- EDP 380D.4 Psychometric Theory and Methods
- EDP 480C.4 Correlation & Regression Methods
- EDP 381C.2 Research Design & Methods for Psychology and Education
Development & Learning Foundation (6 hours)
- EDP 382C.2 Social Psychology
- EDP 382F.3 Life Span Development
- EDP 382D.4 Psychology of Learning
- EDP 382D.6 Motivation and Emotion
- EDP 382D Instructional Psychology
Quantitative Methods Program Courses (30 hours)
- EDP 380D.6 Program Evaluation Models & Techniques
- EDP 380C.8 Data Analysis Using SAS
- EDP 380C Data Exploration and Visualization in R
- EDP 380C Statistical Modeling and Simulation in R
- EDP 380C.14 Structural Equation Modeling
- EDP 380C.16 Hierarchical Linear Modeling
- EDP 380C.12 Survey of Multivariate Methods
- EDP 380C.23 Missing Data Analysis
- EDP 380D.8 Item Response Theory
- EDP 380D.14 Applied Psychometrics
- EDP 381C.14 Causal Inference
Program Electives (12 hours)
An additional 4 QM program electives must also be chosen from the following (or alternative QM program elective approved by Area Chair):
- EDP 380C.18 Applied Bayesian Analysis
- EDP 380D.18 Advanced Psychometrics Research
- EDP 380D.11 Computer Adaptive Testing
- EDP 381E Advanced Item Response Theory
- EDP 381C.12 Meta-Analysis
- EDP 381D Advanced Statistical Modeling
- EDP 380C.22 Analysis of Categorical Data
- EDP 380D.10 Test and Scale Construction
Out-of-Specialization Courses (9 hours)
The Graduate School requires doctoral students to complete 9 hours of coursework outside of their area of specialization. These courses are an opportunity to enhance research/clinical interests and form relationships with out-of-area faculty; course choice must be approved by faculty adviser.
- 1 course (minimum 3 hours) taken outside of the EDP department
- 2 courses (minimum 6 hours) taken either outside of the EDP department, or an EDP program area outside QM.
- At least 1 must be taken for a letter grade
Qualifying Process & Dissertation (12+ hours)
- Qualifying Process: EDP 395R Qualifying Process Research (2 semesters, no later than the semester in which turn in the Qualifying Document)
- Dissertation: EDP 3/6/999W Dissertation, beginning the semester following advancement to candidacy.
En-Route Masters
EDP doctoral students admitted without a master’s in the field must complete an en-route master’s degree before receiving the doctoral degree. See the En-Route Master’s page for requirements.
Doctoral Portfolio Programs (Optional)
Portfolio programs are optional opportunities for doctoral graduate students to obtain credentials in a cross-disciplinary academic area of inquiry while they are completing the requirements for a degree in a particular discipline. A portfolio program usually consists of four thematically related graduate courses and a research presentation.
Faculty
Students are admitted to the program area, and while they are welcome to select individual faculty members for their application, they are not required to do so.
Interested in statistical models with a focus on deriving and evaluating multilevel model extensions and meta-analysis models for educational, behavioral, social and medical science data.
Interests include the development and dissemination of computerized adaptive testing applications in educational and psychological testing and patient-reported outcome measurements.
Research interests focus on using Bayesian statistical methods to employ hierarchical linear modeling, specifically working with longitudinal and mediation data.
Statistical methods related to psychometrics, such as uni- and multi-dimensional item response theory, response time modeling, cognitively diagnostic assessment, and stochastic test design.
Quantitative methods for causal inference, experimental/quasi-experimental design and analysis, causal mediation analysis, clustered and/or longitudinal data analysis.
My principal methodological research interest deals with the various facets of model specification, including, but not limited to, model comparison/selection and model modification methods. With the use of simulation techniques, I examine the perform...
Additional Resources
- Program Starts: Fall, Summer
- Deadline to Apply: December 1
- Credit Hours Required: 86
- Schedule: Full-time enrollment required until admitted to candidacy
- Program Location: On Campus
- GRE Required? Yes
Area Chair
Seung Choi
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