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 PhD programs (currently none of the quantitative faculty are members of the School Psychology PhD 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.
Typical Curriculum for students specializing in Quantitative Psychology
within the Experimental Program:
Notes for the Quantitative Area of Study
Quantitative students will typically take both of PSYC 821 and 823 (or equivalent courses) to cover the fundamental areas of measurement and multivariate statistics. PSYC 824 is offered with a variety of topics and is often taken as an elective.
Taking six of these two hour modules provides a solid background in several substantive areas of psychology, providing the needed training to interact with your non-quantitative colleagues.
Having used both PSYC 821 and 823 above, an additional 22 credit hours (typically 8 classes) of electives and complementary course work are required. These courses will often include electives from a variety of departments around campus.
Elective and Complementary Course Work
Current research topics in quantitative psychology are regularly taught through PSYC 824 (Seminar in Quantitative Psychology) and PSYC 888 (Selected Topics in Psychology). These variable-offerings courses can be repeated for credit under different topics. Recent offerings have included:
- Advanced Methods in Analysis of Neuroimaging Data
- Longitudinal Data Analysis
- Mediation and Moderation
- Multilevel Modeling
- Structural Equations Modeling
In addition, up to six hours of PSYC 889 (Independent Advanced Research) with your advisor may be counted towards your elective credit.
Courses in the Statistics Department
In consultation with the advising committee it is frequently recommended that students take the basic statistics sequence in the Statistics Department, replacing PSYC 709 and PSYC 710 with STAT 700 and STAT 701. This provides the option of receiving a concentration or Master’s degree in Applied Statistics as well as the PhD in Psychology. Other options in the Statistics Department include:
- STAT 702 and 703 – Introduction to Statistical Theory I and II
- STAT 740 – Statistical Computing
These courses cover the technical background necessary to stay abreast of the most recent methods in the literature. Students who wish to be more mathematical may also elect the STAT 712/713 statistical theory sequence (usually taken by M.S. and Ph.D. students in Statistics) instead of STAT 702/703. This opens up several additional electives typically restricted to students in that department.
A variety of other electives are regularly taken in departments across campus, including Statistics (STAT), Biostatistics (BIOS), Management Science (MGSC), and Educational Research and Measurement (EDRM). These include courses in both classical quantitative areas (such as item response theory and structural equations modeling) as well as in more general statistical methods (such as experimental design and nonparemteric methods).
- BIOS 754 – Discrete Data Analysis
- BIOS 825 – Multivariate Biostatistics
- EDRM 712 – Nonparametric Statistics
- EDRM 724 – Design and Analysis of Educational Surveys
- EDRM 728 – Technical Aspects of Tests and Measurements
- EDRM 789 – Principles and Applications of Structural Equations Modeling
- EDRM 812 – Hierarchical Linear Modeling
- STAT 506 – Introduction to Experimental Design
- STAT 517 – Computing in Statistics
- STAT 518 - Nonparametric Statistical Methods
- STAT 530 – Applied Multivariate Statistics
- STAT 770/BIOS 805 – Categorical Data Analysis
- STAT 771/BIOS 770 – Applied Longitudinal Data Analysis
- STAT 775/BIOS 815 – Generalized Linear Models
- STAT 778/EDRM 828 – Item Response Theory
- STAT 790 – Seminar in Statistical Consulting
- STAT 791 – Practicum in Statistical Consulting