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Department of Psychology


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Training in Quantitative Psychology

Psychologists view human behavior as a complex phenomenon, stemming from multiple causes. Although psychological constructs may seem straightforward, they can be challenging to measure and study. Quantitative psychology involves research into methodology, measurement, and statistics as applied to the study of human behavior to address these challenges. 

Area of Emphasis

Quantitative psychology is an area of emphasis in the University of South Carolina Department of Psychology in which students can conduct research and receive training. Quantitative psychologists in the department develop and apply statistical methodology to a wide range of applied problems including, but not limited to, substance use, physical activity/obesity, and neuroimaging. The collaboration between quantitative research and other areas in psychology builds synergy in the department.

 

Advanced Training

At the Ph.D. level there are several opportunities for advanced training in Quantitative Psychology. Applied students from any of the  three Ph.D. programs in the department  can receive additional training in quantitative methods and earn a certificate of concentration in Quantitative Methods for Psychology. Applied students desiring additional technical training may also earn a Concentration in Applied Statistics or a Masters in Applied Statistics from the Department of Statistics. Students interested in Quantitative Methods as a primary training area can work directly with one of the faculty in Quantitative Psychology to earn a Ph.D. as preparation for a career in this area.

 

Quantitative Concentration

The Quantitative Concentration is designed for students doing research in an applied area in one of the three Ph.D. programs who want to take extra methodological courses that complement their area of applied research. The concentration provides an official recognition that the student has completed additional quantitative training in, and potentially outside, the department.

 

Doctoral Training in Quantitative Psychology

Students at USC can train for a career in quantitative psychology by applying to work with quantitative faculty in either the clinical/community or experimental Ph.D. programs (currently none of the quantitative faculty are members of the school psychology Ph.D. program). Students in either program are required to complete all the requirements of that program in conjunction with quantitative courses. The clinical/community program includes fewer elective courses and requires practicum and internship; the experimental program allows much greater flexibility in tailoring a curriculum which matches the quantitative interests of the student. Prospective students should contact the faculty member(s) with which they are interested in working to discuss the best option.

Amanda J. Fairchild

Associate Professor, Member of Clinical-Community and Experimental Ph.D. programs

Dr. Fairchild’s work centers on the development of quantitative methods for the study of physical and psychological health-related behaviors. Much of this work has centered on mediation analysis, or the investigation of third variables that elucidate the relation between predictors and dependent variables. Dr. Fairchild also has interest in the validity and reliability of measurements, as well as effect size measures.

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Svetlana V. Shinkareva

Associate Professor, Member of the Experimental Ph.D. program

Dr. Shinkareva’s research focuses on the development and application of quantitative methods to neuroimaging data. Her current interests include applying machine learning methods to fMRI data to study the neural basis of semantic knowledge representation.

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Alberto Maydeu-Olivares

Professor, Member of the Experimental Ph.D. program

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M. Lee Van Horn

Associate Professor, Member of Clinical-Community and Experimental Ph.D. programs

Dr. Van Horn’s methodological research involves methodology for understanding individual differences in the effects of family, school, and community contexts on development. He also evaluates methodology for assessing the impacts of group randomized trials, intervention trials in which groups (such as schools or communities) rather than individuals are randomized into treatment and control communities.

John Richards

Professor, Member of the Experimental Ph.D. program

Dr. Richards has several areas of methodological / quantitative expertise that are closely integrated with his research on infant attention. He has developed an interesting model of infants looking behavior toward multimedia stimuli (e.g., children's TV viewing). This model borrows its theoretical background from biological models and uses quantitative examination of statistical distributions compared to infants viewing behaviors. A second area of work is the use of quantitative cortical source methods using high-density EEG recording to infer areas of the brain involved in psychological behavior.

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Douglas H. Wedell

Professor, Member of the Experimental Ph.D. program

Dr. Wedell’s quantitative interests revolve around measurement issues related to contextual bias and mathematical models of contextual processes. Within measurement he has investigated reliability and validity issues related to contextual effects on dominance and proximity based measures. His mathematical models are primarily focused on understanding biases in responding, especially related to judgment and choice.

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Brian Habing

Statistics, Associate Professor, Adjunct Member of the Experimental Ph.D. program

Dr. Habing’s psychometric research focuses on theoretical, computational, and applied issues in item response theory, scale construction, and multivariate statistics. His publications include a number of papers on multivariate and nonparametric item response theory, with his research in that area being supported by the National Science Foundation. He is currently co-investigator on an NSF grant studying the simultaneous modeling of dominance/monotone and unfolding/Thurstone items. In addition to his research, he co-created the courses STAT 778/EDRM 828 Item Response Theory and STAT 530 Exploring Multivariate Data courses at USC.

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