Eeg Methods For The Psychological Sciences

[Zebedeo Konig]

Ourtwo-year graduate program in Psychological Science awards a Masters of Arts degree. This program provides students with a solid foundation in scientific research, through a combination of mentored laboratory experience and complementary coursework. There are eight core faculty members in the program, providing the opportunity to gain expertise in cognitive, social, and/or neuroscientific approaches to experimental psychological research. Training will culminate in the proposal and defense of a thesis research project, with the goal of publishing results. Our program is designed to prepare students for further doctoral training and/or careers in academia, biomedical research, business, or clinical practice (see Alumni section for testimonials).

Faculty now benefit from over 14,600 square feet of dedicated research space in the new home of the CSU Department of Psychology: the Union Building on Euclid Avenue. Close proximity between laboratories, faculty and student offices promote collaboration in research. Faculty employ a wide range of research methods and technologies, allowing students to develop an optimal approach for their particular research questions

Faculty in the Quantitative Methods (QM) program train students in state-of-the-art statistical methods and engage in research that develops and applies such methods. Students in the QM doctoral program develop expertise in the principles of research design and in the theoretical foundations and application of advanced statistical models for human behavior. Students work closely on research projects with a faculty mentor throughout their graduate career, and often collaborate with other faculty and students. QM faculty collectively have expertise in factor analysis and structural equation modeling; network analysis; measurement and item response theory; exploratory data analysis; mediation and moderation; longitudinal methods; multilevel modeling; mixture modeling; categorical data analysis; and generalized linear models. Quantitative faculty approach the study of these topics from a variety of angles, such as: developing computational tools to promote the use of new or existing methods; evaluating the performance of such methods under real-world conditions; and applying these methods in novel and sophisticated ways to solve substantive problems. Several QM faculty have substantive specializations in, for example, individual differences, personality psychology, clinical psychology, learning sciences, and developmental psychology, which facilitate intensive investigation of analytic approaches critical to those substantive domains. Students may pursue greater or lesser degrees of substantive psychological training, in addition to quantitative training, depending on their and their advisors' interests.

The QM program is housed within the Department of Psychology and Human Development at Peabody College--a top-ten ranked school of education for the past ten years. This unique context exposes QM students to a variety of applications, methods, and statistical problems that arise in psychological and educational research, as well as the social sciences more generally.

More information about individual faculty's research programs can be obtained from their websites by clicking on their names. Alternately, a list of QM faculty is available here. Prospective students are encouraged to contact core QM faculty with shared interests to ask questions about the program. Core QM faculty recruit and train Ph.D. students through the QM program.

The program maintains its own quantitative computer lab, and additionally individual faculty have labs and computing resources that support their research programs. There are also computing labs in the department and elsewhere in Peabody College that are supplied with statistical software often used for classroom teaching. Special funds for research-related software and computing equipment, as well as external workshop and conference travel, are available to QM students.

QM doctoral program graduates are prepared for faculty positions in academic settings, methodology positions in basic or applied research centers, or methodology positions in industry. Students work together with their advisor and advisory committee to refine their career goals, and tailor their research, coursework, and teaching experiences accordingly. The American Psychological Association reports that there are far more jobs for doctoral students trained in quantitative methods in psychology than there are applicants. Further information can be found here, here, and here.

The QM program is designed to lead to a Ph.D. degree within 5 years. In the first two years, students take a series of fundamental methods courses and begin working on research with their advisor. To build students' oral presentation skills, students present their research to the program on a yearly basis. Students who did not enter with a full year of calculus also complete such coursework in the Mathematics Department during this time. In their third year, students complete their masters thesis and continue research in collaboration with their advisor and others, while furthering their expertise with an individualized set of advanced coursework. Students take an exam in their third or fourth year that is based on reading lists related to content in courses they have taken up until that point. In their fourth and fifth years students finish their coursework and conduct a dissertation project under the guidance of their advisor and other committee members, while building additional independent research and/or teaching skills relevant to their particular career goals.

Doctoral applicants admitted to the QM program receive a guaranteed 5 years of stipend and tuition support, which usually takes the form of a combination of research assistantships and/or teaching assistantships in quantitative courses (for instance, the introductory graduate statistics sequence). Additionally, QM students have a successful track record of obtaining prestigious NSF fellowships. Senior students routinely also may obtain other kinds of stipends as statistical analysts or consultants for various research projects and grants on campus; these opportunities serve as valuable supplementary training experiences. Some students also serve as teaching instructors for their own section of an undergraduate statistics course or undergraduate measurement course in order to deepen their teaching credentials. Application instructions are available here.

In Spring 2014, the QM program launched a terminal M.Ed. in Quantitative Methods. This program is distinct from our longstanding research-focused Ph.D. program. More information about the goals and expectations for applicants to our M.Ed. program can be found here.

Doctoral students outside the QM program may elect to minor in quantitative methods. This formal minor involves taking four advanced methods courses from the QM program beyond the first year required graduate statistics sequence (6 courses total). The minor requires a 3.5 average GPA (for all 6 minor courses), with no grade below a B. The minor provides students with exceptional training in the application of complex psychometric and statistical procedures and provides students with skills that can enhance the quality of their research program over the course of their career. Many students find that the credential of a graduate minor in quantitative methods is a valuable asset in the pursuit of research-oriented academic positions or quantitatively-oriented industry positions after graduation. Detailed information on minor requirements can be obtained from the Psychological Sciences graduate student handbook. For more information, contact Kris Preacher.

The QM program offers a weekly Quantitative Methods Colloquium Series which covers novel methodological advances, cutting-edge applications of quantitative methods, inclusivity in QM, teaching pedagogy in QM, QM professional development activities, QM outreach, and QM workshops. The QM colloquium series features a mix of external speakers from different settings (e.g., academia and industry) and different stages of their careers in order to expose our QM students to a variety of career paths and perspectives. Each semester our QM forum also contains internal program speakers, QM students and QM faculty, to allow us to share our research with, and gain feedback from, our colleagues. For more information on the QM Colloquium please visit the Colloquium schedule.

At least once per year the QM Colloquium Series features an Open House where statistical consulting problems presented by Peabody faculty guest(s) receive a program-level discussion. Additionally, our QM program offers a statistical consulting course on a yearly basis to which Peabody faculty can submit statistical problems to serve as student projects. QM faculty also maintain a listserv (qmg...@vanderbilt.edu) to which Peabody faculty can submit statistical problems that are limited in scope. Submitted questions will first be considered for open house or course project slots and secondarily for a graduate assistant to the QM faculty for further attention.

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