Psychology (Quantitative Research Methods), PhD

Quantitative Psychology

The quantitative concentration focuses on the broad class of quantitative and methodological issues that arise in the conduct of both basic and applied psychological research. Core faculty members in Quantitative are typically affiliated with other doctoral program areas which further supports the training of students of quantitative methods against a backdrop of methodological issues associated with the development of the substance of psychological science.

Research Activities: Faculty and doctoral students undertake methodological research of direct relevance to substantive psychology. New methodologies are developed and applied in three broad areas: (1) modern approaches to measurement of psychological constructs; (2) research;design; and innovations; and (3) data analysis and techniques, including both those with established utility for psychological data and those enjoying only recent or more rare use in psychology. Quantitative faculty currently have ongoing research programs in the development of statistical methodologies for mediation analyses, multilevel modeling, the evaluation of the performance of structural equation models, latent class analyses, research design strategies under conditions of self-selection and attrition, cross-group measurement equivalence, measurement bias in psychological tests, missing data analyses, multitrait-multimethod analyses, testing and interpreting statistical interactions and the longitudinal growth modeling of psychological constructs.

Career Goals:The quantitative concentration is committed to training the next generation of psychological methodologists, who will make contributions in developing methods in the areas of measurement, design, and analysis, and to evaluating the utility of new and existing methods for use in psychological research. Graduates are prepared for faculty positions as quantitative psychologists in departments of psychology, for methodologist positions in large research centers, and for positions in industry. Graduates of the program hold faculty positions at major research universities and research centers. 

Prospective Students

Methodological/Substantive Specializations: Within their programs of study, quantitative students may develop methodological and substantive specializations that provide a unique combination of expertise in a substantive area coupled with intensive study of methodologies central to the substantive area. This option of combining specializations provides the opportunity to develop focused research career tracks within the broad area of quantitative methods. For example, prevention research in mental health and health is an area of strength within the psychology department, in which quantitative faculty are centrally involved; this leads to the possibility of specialization in prevention research methodology. Specializations in applied social research and developmental research are among the possibilities as well.

Mentorship: Across our faculty there is ample and easy access to academic and research advisors/mentors. Further, there is great flexibility in that students may work with a variety of faculty during the course of their training.

Research Experience: Quantitative students participate in research throughout their graduate careers to help foster an active record of publication while in graduate school. Research experience is gained through the master's thesis and dissertation. In addition, students may participate in research independent of the master's thesis and dissertation in collaboration with a variety of faculty members.

Quantitative students are in very high demand by faculty to work in their laboratories as quantitative/computing experts and there are several large scale externally funded research programs housed within Psychology that provide a diversity of opportunities. Further, experience in the handling of large scale data sets is also highly desirable as a job qualification.

Computing Experience: Training in statistical computing is both formal, in quantitative classes, and informal, in conjunction with research projects. Special computing approaches (e.g., Monte Carlo simulation) are learned through work with the research advisor, often as part of the master's thesis or dissertation. The Department of Psychology houses two state-of-the art computing labs with a variety of statistical software packages, and the university provides web-based access to popular software packages through a Citrix server.

Teaching:  This experience is highly desirable as a job qualification for academic positions. Students may gain teaching experience by serving as teaching assistants in a progression of undergraduate, introductory graduate, and advanced graduate courses, under the supervision of quantitative faculty who are teaching the course. As a capstone experience, students can teach their own section of a course, under the supervision of a quantitative faculty member.


Note that the application forms list the quantitative program as a separate option with its own Plan Code: LAPSYQUPHD.  This is distinct from our other Psychology doctoral programs. When completing the application, select QUANTITATIVE RESEARCH METHODS. 


Admission: Students are admitted directly to the PhD program with the expectation that the student will progress through a master's (M.A.) degree to the PhD.

Content of Training: Students receive a mix of training in quantitative methods and in substantive psychology, with the extent of substantive training, above and beyond quantitative training, dependent on the interest of the individual student. Within the Department of Psychology we offer the full complement of course work in analysis of variance and regression, multivariate analysis, structural equation modeling, modern measurement, experimental and quasi-experimental design, with additional more specialized training in topics of interest including regression graphics, methods in prevention research, mediation analyses, missing data analyses, multilevel modeling, latent class analyses and longitudinal growth modeling. Additional quantitative course work is available in other departments on campus, and cooperative arrangements with these departments are well established. The quantitative curriculum and program requirements are given below.

Quantitative Curriculum and Program Requirements: The quantitative curriculum is structured into a series of progressively more advanced courses. New quantitative/methodological courses may be implemented under an omnibus number (PSY 591) at the interest of the faculty. The list below includes our current offerings.

Required Courses (7 courses, 21 credits):

  • PSY 530 Analysis of Variance
  • PSY 531 Multiple Regression Analysis
  • PSY 532 Analysis of Multivariate Data
  • PSY 533 Structural Equation Modeling
  • PSY 534 Psychometric Methods
  • PSY 555 Experimental and Quasi-Experimental Designs
  • PSY 591 Quantitative Seminar

 Psychological Methodology Electives (3 courses, 9 credits):

  • PSY 536 Methods in Prevention Research
  • PSY 537 Longitudinal Growth Modeling
  • PSY 538 Advanced SEM
  • PSY 539 Multilevel Modeling
  • PSY 540 Missing Data Analysis
  • PSY 543 Mediation Analysis
  • PSY 544 Item Response Theory
  • PSY 591 Advanced Regression and Graphics
  • PSY 591 Data Mining in Psychology 2

In addition to the courses listed above, elective quantitative courses may be taken outside the Department of Psychology across the university. Topics of interest include, but are not limited to, categorical data analysis, econometrics, time series analysis, exploratory data analysis, epidemiology, survey sampling, and mixed models.

Substantive Coursework (2 courses, 6 credits). Students are expected to take two courses in a substantive area of psychology, of which one may be a research methods course in a substantive area.

Additional substantive or methodological electives (2 courses, 6 credits) include readings and conferences; and special research topics.

Milestone Courses include PSY 592: Master’s Research (6 credits); PSY 599: Master’s thesis (6 credits); PSY 792: Post-Master’s Research (12 credits); and PSY 799: Dissertation (12 credits) 

Total: 84 credits 


Program Milestones

Master's Thesis: The master's thesis is typically undertaken in the second year. It is an original piece of research, closely supervised by the research advisor. The student defends the thesis before a committee consisting of his or her advisor and two additional faculty members. The thesis leads to the M.A. degree. The master's degree also requires a minimum of 30 semester hours of graduate credit. In lieu of a thesis, students entering with an M.A. complete a methodological research project during their first year.

Comprehensive Paper and Examination: Near the end of completion of course work, students concentrate much of their effort on the development of a written comprehensive paper. This paper is typically a scholarly review of a substantial area of methodology (e.g., longitudinal growth modeling, survival analysis), plus discussion of issues and future directions. The student, in the process of developing the paper, becomes an expert in the area. The paper is often the basis of the doctoral dissertation. Again, the student works in close conjunction with a research advisor, as well as with three additional faculty members, the four of whom constitute a comprehensive examination committee. The student defends the comprehensive paper before this committee; this defense constitutes the comprehensive examination. There is no other comprehensive written examination.

Doctoral Dissertation: The doctoral dissertation is an extensive piece of original research which demonstrates the capability of the student to act as an independent scholar in quantitative methods. The dissertation is closely supervised by the research advisor and three additional faculty members, who constitute the dissertation committee. The dissertation process begins with the dissertation proposal, a written document that provides a comprehensive scholarly introduction to the research and a complete description of the research to be undertaken. It is defended before a dissertation committee. Once the oral defense of the dissertation proposal is completed, the student is admitted to Ph.D. candidacy by the Graduate College. The research proposed must make an original contribution to knowledge in the field of psychology. The dissertation itself serves to demonstrate student's proficiency as an independent investigator. Defense of the dissertation is a two-stage process. First, the psychology department requires a "data meeting," a working meeting in which the empirical and/or analytical outcomes are reviewed by the whole committee. Any further needed work is discussed. Successful completion of this meeting is required before the student prepares the final dissertation. The student then defends the dissertation in a final oral examination. The interim step of the data meeting, unique among psychology departments, helps greatly to assure that the dissertation that is presented for final defense is adequate for approval. 



CORE FACULTY:  Aiken   Edwards   Grimm   MacKinnon   McNeish   West

EMERITUS FACULTY:  Braver   Knight

Leona Aiken, PhD, President's Professor. Methodological interests: Interactions in multiple regression analysis; design innovations (e.g., retrospective pretests in program evaluation, utilization of multiple designs in common settings to estimate treatment effect sizes). Substantive interests: Health psychology, prevention interventions to enhance women's health. Past Associate Editor, American Psychologist.

Mike Edwards, PhD, Associate Professor. Research Interests: item response theory (IRT), computerized adaptive testing (CAT), factor analysis (exploratory, confirmatory, and everything in between), psychometrics (especially validity), measures of model fit, local dependence, and structural equation modeling (SEM). Current Associate Editor: Multivariate Behavioral Research. Current Editorial Board Member: Archives of Scientific Psychology, Psychological Methods, & Quality of Life Research.

Kevin Grimm, PhD, Professor. Methodological Interests: Longitudinal data analysis, structural equation modeling, growth modeling, multiple group analysis, and growth mixture models. Substantive Interests: Cognitive development, achievement, and impacts of non-academic skills on achievement. Lab: Health and Developmental Methods Lab

David MacKinnon, PhD, Foundation Professor. Methodological Interests: Statistical methods in prevention research; development and application of mediation analysis; analysis of variance and categorical data analysis methods. Substantive interests: Effects of warnings on behavior, applied cognitive psychology, and the mechanisms by which prevention programs are effective. Lab: Research in Prevention Lab.

Daniel McNeish, PhD, Assistant Professor. Methodological Interests: Models for correlated and clustered data, mixed effects models, small sample analysis, growth models, structural equation models, and Bayesian methods. Substantive interests: Educational and clinical psychology.

Stephen West, PhD, Professor. Methodological interests: Experimental, quasi-experimental and longitudinal designs; causal inference, structural equation modeling, multiple regression analysis, mediation analysis, statistical graphics and exploratory data analysis, longitudinal and multilevel data analysis. Substantive interests: personality research, applied social psychology, particularly prevention related issues in health, mental health, substance abuse, and education. Currently Associate Editor: Multivariate Behavioral Research. Past Editor: Psychological Methods.

Emeritus Faculty

Sanford Braver  PhD, University of Michigan. Methodological Interests: Research designs that optimize generalizability; statistical approaches to detecting mediation; time series analyses; issues regarding missing data or self-selection biases; experimental designs for field settings; mutually canceling effects in research. Substantive interests: Family psychology, prevention research, fathering behaviors, conflict resolution.  

George Knight, PhD, Professor, Riverside. Methodological interests: Cross-group measurement equivalence, research methods for studying diverse populations, multiple regression, and meta-analysis. Substantive interests: prosocial behavior; development of cooperative, competitive and individualistic behavioral styles; cross-cultural issues; and the development of ethnic identity in Mexican American children.

Quantitative Research Laboratories

News & Highlights

Kevin Grimm is the 2017 recipient of the Cattell Early Career Award from the Society of Multivariate Experimental Psychology (SMEP) for outstanding early career contributions to multivariate experimental psychology.

Stephen G. West is the 2017 recipient of the Eber Distinguished Service Award from the Society of Multivariate Experimental Psychology (SMEP) for his years of distinguished service as editor of Multivariate Behavioral Research.

 David MacKinnon has been elected president of Division 5 of the American Psychological Association for 2017-2018. Division 5 is the Division of Quantitative and Qualitative Methods.

Stephen G. West is the 2017 recipient of the Samuel J. Messick Award for Distinguished Scientific Contributions within the Field of Quantitative Research Methods. This award is presented annually “to honor an individual who has a long and distinguished history of scientific contributions within the field of quantitative research methods.”

Stephen G. West received the 2017 APA Board of Educational Affairs for Outstanding Graduate Teaching of Psychology as a core STEM Discipline. This award, given only every three years, “recognizes the contributions of a graduate level professor whose teaching exemplifies psychology as a core science among the science, technology, engineering and mathematics (STEM) disciplines.”

Hanjoe Kim (2017 Ph.D.) has accepted a position as an Assistant Professor of Psychological Health and Learning Sciences in the College of Education at the University of Houston.

Katerina Marcoulides (2017 Ph.D.) has accepted a position as an Assistant Professor of Informatics and Statistics in the College of Education at the University of Florida.

Degree Offered

Psychology (Quantitative Research Methods), PhD
Liberal Arts & Sciences, College of


Plan of Study

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