A range of courses in Quantitative
Psychology are offered regularly. The Quantitative Foundations
area includes one semester of a basic psychological statistics course, which is
offered semesterly. The Quantitative Core is a more intense series of
courses in fundamental quantitative areas, and currently includes Test
Theory, Multivariate Methods, Multilevel Modeling I, Nonparametrics, Factor Analysis, Categorical
Methods, and Structural Equation Modeling I. The Quantitative
Concentration area focuses on a wide range of more specialized
applications, and currently includes courses in Clustering and
Classification, Meta-analysis, Multidimensional
Scaling, Structural Equation Modeling II, and Longitudinal Modeling. In
addition, the Quantitative Proseminar is an ongoing discussion
series covering advanced topics and emerging issues in the field.
Courses will be added to these current offerings as the program
continues to add faculty. In addition, students complete at least one
semester of a Research Methodology course. Numerous methodology
courses associated with the different substantive foci in the department
are available.
The minor concentration requirement is
fulfilled by taking three or more courses in a specialized area of
psychology (e.g., cognitive, developmental, health, social, and
psychopathology), education (e.g., testing, evaluation), mathematical
statistics, or a tailored curriculum that meets the goals and objectives
of the student (e.g., business).
All Graduate School requirements, including an
M.A. thesis, written and oral
comprehensive examinations, FLORS,
dissertation thesis, and final defense, apply to the Quantitative
Psychology Program. The masters and dissertation theses may be empirical
studies of quantitative issues, original quantitative innovations, or
cutting-edge applications that utilize best-practice quantitative
methods on a topic related to the student’s ultimate career objectives.
For the
Comprehensives requirement, students have the choice of writing a paper,
conducting an in-depth project, or taking a comprehensive examination.
Students then deliver a public presentation of their work to their
committee members, which functions as the oral component of the
comprehensives. For the paper options, students can write a review paper
covering a topic with either a substantive or quantitative focus.
Students can also choose to conduct a meta-analysis of a topic with
either a substantive or quantitative focus. For the in-depth project
option, students can prepare a full set of lecture materials (e.g.,
PowerPoint slides, written lectures, homework assignments, etc.) for a
quantitative course that would be suitable for offering at the graduate
level. For the comprehensive examination option, students would work
with their committee to prepare a reading list and a set of questions
designed to demonstrate mastery of the material. Written exams typically
are conducted in four 3-hour blocks of time. The
FLORS requirement is typically
fulfilled by demonstrating competency in one or more computational
languages to enable specialized studies in quantitative methods.
Proficiency is determined by a review of the student’s body of work by
the program director and the student’s dissertation advisor.
| Quantitative Training: |
Required hours/# Courses |
Specific Course Numbers |
| Quantitative Foundations |
4 hours |
790 - Statistical Methods in Psychology I
Elementary distribution theory; test;
simple regression and correlation; multiple regression and multiple correlation;
curvilinear regression; logistic regression; general linear model. Applications across the
behavioral and social sciences are emphasized. Course consists of three hours of lecture
and a required one-hour lab session where computing applications are taught. Prerequisite:
Abeginning course in statistics and graduate standing, or consent of instructor. LEC
|
|
| Area-specific Methodology |
1 course
(3 hours minimum) |
815 - Developmental Research Design
Coverage of the philosophy and basic
principles of group-design research, with a special emphasis on
designs that are appropriate for developmental studies. Designs for
both experimental and quasi-experimental research are covered, and
appropriate statistical procedures are presented concomitantly with
the designs. Individual-difference analyses and statistical control
issues are also addressed. LEC
|
816 - Neuroimaging Research Design
Course covers research
design and analysis issues for event-related potential (ERP) and functional
magnetic resonance imaging (fMRI) studies. Repeated measures, statistical parametric
mapping, principal components analysis, and independent components analysis
techniques are covered. Both practical and theoretical aspects of these statistical
techniques will be explored in Matlab environment. Matrix algebra recommended
but not required. Prerequisite: PSYC 790 and 791 or equivalent are required. LEC
|
818 - Experimental Research Methods
Systematic discussion of the techniques of
research in social psychology, with practice in the utilization of
selected methods. Prerequisite: One course in social psychology in
addition to introductory social psychology. LEC
|
819 - Field/Evaluation Research Methods
Basic
principles and practices of field methods in basic and applied research in social
psychology and related fields; relationships between field and laboratory studies;
special emphasis on survey and evaluation research methods and study designs;
client and respondent relationships; research and public policy. LEC
|
|
| Quantitative Core |
7 courses
(27 hours minimum) |
791 - Statistical Methods in Psychology II
Continuation of PSYC 790. Oneway
analysis of variance, linear trends, contrasts, post hoc tests; multi-way analysis
of variance for crossed, blocked, nested, and incomplete designs; analysis of covariance;
repeated measures analysis of variance; general linear model. Applications
across the social, educational, and behavior sciences are emphasized. Course consists
of three hours of lecture and a required one-hour lab session where computing applications
are taught. Prerequisite: PSYC 790 or equivalent, or consent of instructor. LEC
|
887 - Factor Analysis
This course covers the theory behind, and application
of, exploratory factor analysis. Topics include a review of multiple linear regression
and matrix algebra. In-depth coverage is devoted to diagrams, model
specification, goodness of fit, model selection, parameter estimation, rotation methods,
scale development, and sample size and power issues. Extensions to confirmatory
settings are elaborated. Both the theory underlying factor analytic techniques
and hands-on application using software are emphasized. Applications across the
social and behavioral sciences are emphasized. Course consists of three hours of
lecture and a required one-hour lab session where computing applications are
taught. Prerequisite: PSYC 790 and 791 or equivalent, or consent of instructor. LEC
|
889 - Nonparametric Statistical Methods
Topics include a review of parametric statistics,
sampling distributions, the logic of hypothesis testing, and motivations for
using nonparametric techniques. In-depth coverage will be given to distributionfree
procedures, sign tests, contingency tables, median tests, chi-square and other
goodness-of-fit tests, rank correlations, randomness tests, Monte Carlo methods,
resampling methods, tests of independence, 1-sample, 2-sample, and k-sample
methods, permutation tests, and function smoothing and splines. There will be an
emphasis on the theory underlying nonparametric methods. Applications across
the behavioral and social sciences are emphasized. Course consists of three hours
of lecture and a required one-hour lab session where computing applications are
taught. Prerequisite: PSYC 790 and 791 or equivalent, or consent of instructor. LEC
|
892 - Test Theory
This course takes a unified approach (from classical
and modern test theory) to the topic of measurement in the behavioral and social
sciences. Content covered includes the construction and administration of psychological
tests (examples include tests of intelligence, achievement, and personality);
practice in test construction, administration, and validation; and how to assess the
reliability and generalizability of an instrument. Applications across the social and
behavior sciences are emphasized. Course consists of three hours of lecture and a
required one-hour lab session where computing applications are taught. Prerequisite:
PSYC 790 and 791 or equivalent, or consent of instructor. LEC
|
893 - Multivariate Analysis
Introduction to the central methods used in
the analysis of multivariate data. Includes linear transformations, multivariate
analysis of variance, multivariate multiple regression, discriminant analysis,
canonical correlation, factor analysis, and an introduction to methods for clustering
and classification. Applications across the behavior and social sciences are emphasized.
Course consists of three hours of lecture and a required one-hour lab
session where computing applications are taught. Prerequisite: PSYC 790 and
PSYC 791 or equivalent, or consent of instructor. LEC
|
894 - Multilevel Modeling I
Statistical methods for modeling multilevel
(hierarchically structured) data. Topics include a review of ordinary least squares
regression analysis, random effects ANOVA, intraclass correlation, multilevel regression,
testing and probing interactions, maximum likelihood estimation, model
assumptions, model evaluation, and the analysis of longitudinal data. There will
be a heavy emphasis on the theory underlying multilevel modeling techniques
and hands-on application using software. Applications across the social, educational,
and behavior sciences are emphasized. Course consists of three hours of
lecture and a required one-hour lab session where computing applications are
taught. Prerequisite: PSYC 790 and 791 or equivalent, or consent of instructor. LEC
|
895 - Categorical Data Analysis
Multivariate analyses of count data. Error
models, statistical inference, loglinear models, logit models, logistic regression. Homogeneity,
symmetry, and selected other topics. Applications across the behavioral
and social sciences are emphasized. Course consists of three hours of lecture and a
required one-hour lab session where computing applications are taught. Prerequisite:
PSYC 790 and PSYC 791 or equivalent, or consent of instructor. LEC
|
896 - Structural Equation Modeling I
Introduction to statistical methods for
modeling latent variables. Topics include a review latent variables, covariance structures
analysis, mean structures analysis, confirmatory factor analysis (CFA), structural
equation modeling (SEM), multiple group CFA, longitudinal CFA, longitudinal
SEM, Hierarchical CFA, and Multi-trait Multi-Method SEM. Applications across
the behavioral and social sciences are emphasized. Course consists of three hours of
lecture and a required one-hour lab session where computing applications are
taught. Prerequisite: PSYC 790 and 791 or equivalent, or consent of instructor. LEC
|
|
| Quantitative Concentration |
3 courses
(9 hours minimum) |
990 - Clustering and Classification
Statistical methods for
identifying classes, clusters, and taxa. Topics include k-means, discriminant analysis,
hierarchical clustering algorithms, additive trees, neural network models for
clustering, latent class models, finite mixture models, and models for skills/cognitive
diagnosis. Applications across the social and behavior sciences are emphasized.
Prerequisite: PSYC 790 and PSYC 791 or equivalent, or consent of instructor. LEC
|
991 - Longitudinal Modeling
Reviews and contrasts various statistical
methods for the analysis of change. Course focuses on various techniques to analyze
longitudinal (repeated-measures) data beyond the repeated-measures ANOVA
framework. Techniques covered included latent change scores, latent difference
scores, individual-differences modeling of latent residual and change scores, intraindividual
differences modeling (e.g., growth curve, mixed modeling) and growth
mixture modeling. Applications across the behavioral and social sciences are emphasized.
Prerequisite: PSYC 896 or equivalent, or consent of instructor. LEC
|
993 - Advanced Quantitative Topics
996 - Structural Equation Modeling II
Continuation of PSYC 896. Advanced
applications of modern methods for testing hypotheses on multivariate
correlational data in the behavioral and social sciences. Topics include advanced
confirmatory factor analysis, mediation and moderation among latent variables, latent
growth curve modeling, and other latent variable mean and covariance structures
analysis techniques. Applications across the behavioral and social sciences are
emphasized. Prerequisite: PSYC 896 or equivalent, or consent of instructor. LEC
|
Advanced courses offered in other departments/schools may also be taken with director’s consent.
|
| Quantitative Proseminar |
6 semesters
(6 hours minimum) |
Offered as 1 unit of 993 per semester |
| Minor Concentration |
3 courses
(9 hours minimum) |
e.g., Cognitive Psychology, Developmental Psychology, Health Psychology, Social Psychology, Education, Mathematical Statistics. |
| Additional Graduate School Requirements: |
|
|
| FLORS |
The FLORS requirement typically is met by demonstrating competence
in one or more computational languages, enabling specialized study
in quantitative methods. |
Proficiency is determined by a review of the student’s body of work
by the program director and the student’s dissertation advisor at
the completion of the written comprehensives |
| MA Thesis |
1-9 hours + public defense; typically completed by end of 2nd
year of training |
3-person committee |
| Comprehensives (Written
and Orals) |
Review paper, a meta-analysis, elaborate project, or written
exam + public defense; typically completed by end of 3rd
or early in 4th year of training. |
5-person committee with one outside member |
| Dissertation Thesis |
1-12 hours + public defense |
5-person committee with one outside member |
| Total hours |
58 non-thesis hours (15 courses) |
|
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