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Curriculum

The Quantitative Psychology Doctoral Program is intentionally very flexible to allow tailoring to each student’s background and interests. Here we describe the coursework, milestones, and a sample time line for degree completion.

Coursework

There is not a fixed sequence of quantitative courses that all students in the program must follow, although there is a general framework described below. The Department of Psychology and Neuroscience has several course requirements that students across programs must satisfy. In addition, students may choose to complete a minor or masters in another department as part of their course of study.

  1. All students must complete PSYC 830 (Statistical Methods in Psychology I) and PSYC 831 (Statistical Methods in Psychology II) with a grade of P or higher. A student may request a waiver for one or both of these classes if sufficiently similar classes have been taken previously. Any such request will be evaluated by the Director of the Lab with input obtained from the student’s advisor and the current instructors of PSYC 830 and PSYC 831.
  2. All students must complete four specific classes with a grade of P or higher: PSYC 839 (Quantitative Research Methods), PSYC 842 (Test Theory and Analysis), PSYC 844 (Structural Equation Modeling), and PSYC 846 (Multilevel Modeling). The expectation is that all four courses will be taken within the Department of Psychology and Neuroscience. Under certain acceptable circumstances (e.g., course unavailability, enrollment in a cross-listed course), a student may request that an equivalent course offered by another unit on campus be applied to fulfill this requirement. This request will be evaluated by the current Director of the Lab with input obtained from all Quantitative faculty.
  3. All students must complete four additional classes with a grade of P or higher that are offered within the Quantitative Psychology Program beyond those defined in points #1 and #2 above. The selection of the specific courses to be taken are determined by the student and their advisor and will be in part determined by the rotating and sometimes only occasional schedule of when the course is offered. Examples include (but are not limited to) Longitudinal Structural Equation Modeling, Item Response Theory, Categorical Data Analysis, Graphical Analysis, Computational Statistics, Intra-Individual Analysis, Mixture Modeling, and Machine Learning, as well as other advanced topics that might be offered in any given year. One of the four required classes can be obtained with the successful completion of three one-hour seminars in Advanced Topics in Quantitative Psychology; additional seminars may be taken, but these do not further count towards this requirement.
  4. All students are expected to regularly attend and actively participate in Quantitative Forum, held from 12:00-1:00 each Monday. The Forum is a weekly meeting of all faculty and graduate students and consists of research presentations and discussions of professional development issues such as ethics, grant writing, CV development, and journal reviewing. Formal registration is not required.
  5. The requirements set forth above apply to all graduate students regardless of the additional pursuit of minors or masters in other units on campus (e.g., BIOS, STOR). If a student is not formally pursuing an external minor or masters, it is expected that, assuming availability, the required courses defined above will be completed by the end of the third year of study. If a student is formally pursuing an external minor or masters, it is expected that the required courses defined above will be completed by the end of the fourth year of study. All students are strongly encouraged to complete these requirements in a timely fashion.

For more information regarding courses, please review the current Graduate Record.

Milestones

There are three core milestones that make up the doctoral training program in Quantitative Psychology. These are the master’s thesis, the comprehensive doctoral exams, and the doctoral dissertation.

The Master’s Thesis: The first program milestone is the master’s thesis (or more simply, the masters). The masters thesis is not a requirement of the Graduate School nor of the Department, but it is a requirement of the Quantitative Program. The masters typically represents a unique and novel research contribution to some topic within the quantitative sciences. The thesis can take many different forms ranging from analytic developments to computer simulation to advanced data analysis. The particular specification of the thesis is typically established between repeated meetings between the student and the primary advisor.

Comprehensive Exam: The comprehensive exam (or “comps”) is the second academic milestone in the graduate training program in Quantitative Psychology. The exam consists of three written papers related to three specific topics selected by the student with guidance from the exam committee. The reading phase may be no shorter than 1 month and no longer than 4 months and the writing phase is 28 days. Although there are no fixed dates when the reading or writing phase must begin, students must be mindful that committees are not active during the summer or University holidays or breaks. The written exam responses are evaluated by the committee as meeting requirements for pass with distinction, pass, or fail. If an exam is scored as pass with distinction or pass, the student is promoted to doctoral candidacy and proceeds to the final dissertation stage of the program. If an exam is scored as fail, the student may re-take the exam one time.

Doctoral Dissertation: The doctoral dissertation is the capstone to graduate training. The intent and structure of the dissertation is very similar to that of the master’s project although is larger in scope and has much greater expectation for unique and novel contribution. The dissertation represents a unique and novel research contribution to some topic within the quantitative sciences. Like the masters, the dissertation can take many different forms ranging from analytic developments to computer simulation to advanced data analysis. However, there is much greater emphasis placed on novel developments and unique contributions. The particular specification of the thesis is typically established during repeated meetings between the student and the primary advisor and other faculty in the Lab as needed.

The format of the dissertation can take one of two general structures, the choice of which is determined by the student and advisor with input from the dissertation committee. The first is the more traditional format in which the dissertation is presented as a single cohesive document in which there is a continuous presentation of material from start to finish. The second is a multi-chapter format in which the dissertation consists of a general introduction, three distinct chapters, and an integrated discussion. The chapters represent individual papers that are cohesively related to the broader dissertation topic but can stand alone in structure and content.

Sample Timeline

For students entering the program without significant prior course credit or the transfer of a master’s degree, the program is typically navigated in five years. It is possible to complete the program in four years, although this is not common. Further, funding is not guaranteed after the fifth year of study and thus students are strongly advised to complete their requirements in a timely fashion.

Each student follows a time line that is best for their own course of study. A typical time line is:

  • Year 1: required coursework, TA or RA responsibilities, and orienting to new research projects and working with primary advisor
  • Year 2: required coursework, TA or RA responsibilities, successfully proposing masters project by the end of the second year
  • Year 3: fewer courses, TA or RA, successful defense of masters project, presentation of masters results at professional conference or publication outlet, beginning of comprehensive exams, possibly writing a pre-doctoral fellowship application
  • Year 4: fewer or no courses, TA or RA or possibly a fellowship, completion of comprehensive exams, beginning of dissertation proposal with goal of defending proposal by end of fourth year
  • Year 5: one or no courses, TA or RA, completion of dissertation project, presentation of dissertation results at professional conference or publication outlet, search for post-doctoral training opportunities or employment following completion of the program

This is just one example of a time line of study, although some close facsimile is necessary in order to complete the program within a five-year period.

Individual Development Plan

With guidance from their advisers, students will develop and regularly update an Individual Development Plan (IDP) to help evaluate competencies, articulate short and long-term career goals, and direct graduate training goals. The IDP should be completed/updated on at least an annual basis as a component of student evaluation but will be most useful if revisited on a more regular basis, for instance at the start, midpoint and end of each semester, to track progress toward training goals.

There is an annual evaluation of all students conducted by the full faculty of the Quantitative Program that centers on the IDP as well as the Curriculum Vitae (CV) for the student. The CV should include information on publications, conference publications, and software development, expertise with programming languages and statistical packages, and teaching experience. The IDP and CV should be updated and submitted for evaluation by April 1 of each academic year.  Students will receive a letter from the Program Director following the annual evaluation that summarizes the advice of the faculty with respect to the students’ training goals and progress within the program.