Fall 2008

STAT530, Exploring Multivariate Data

Instructor: Brian Habing (habing[at]stat.sc.edu)

Abstract: To introduce students with a variety of statistical backgrounds to the basic ideas in multivariate statistics. It will cover the assumptions, limitations, and uses of basic techniques such as cluster analysis, principal components analysis, and factor analysis as well as how to implement these methods in R, SAS, and SPSS. Instead of theoretical development, the focus will be on the intuitive understanding and applications of these methods to real data sets by the students.

Prerequisites: STAT 515 or PSYC 228 or MGSC or equivalent.

PSYC 709, Quantitative Methods for Behavioral Data I

Instructor: M. Lee Van Horn (vanhorn[at]sc.edu)

Time: MW 1:00 – 2:15, F 1:25 – 3:25

Abstract: This graduate level course is meant to provide Ph.D. students in psychology with the skills to be effective consumers and users of statistics. The focus will be on understanding the statistics most commonly used in psychology and being able to evaluate and critique their use. The course will emphasize the use of the General Linear Model to conduct ANOVA and regression analyses. Students will learn to use these basic statistics as a tool for testing their own research questions. Key goals will be understanding statistical models and their assumptions as well as the application of those models to real world data in both experimental and non experimental contexts.

Prerequisites: Because of space limitations this course sequence is typically only open to graduate students in the Department of Psychology.

PSYC 824: Computational Methods in Psychology

Instructor: Svetlana V. Shinkareva (Shinkareva[at]sc.edu)

Time: Mondays 10:10 - 1:10

Place: LeConte 303

Abstract: This course is intended for students conducting research in psychology and related fields. Students will become familiar with computational and statistical methods and will exhibit a high level of proficiency towards the application of these techniques in the students own area of research. Students will learn Matlab, which is a high level programming language that offers flexibility to analyze and visualize data. This software is capable of implementing algorithms and applications, especially for computationally intensive tasks and large data sets. Matlab is extensively used in the analysis of EEG, eye tracking, fMRI and speech processing data, among other applications.

Prerequisites: Students should be familiar with basic statistical methods (PSYC 709, 710 or equivalent) or must obtain the consent of the instructor. No prior knowledge of Matlab or matrix algebra is required.

PSYC 888, Introduction to Statistical Mediation Analysis

Instructor: Amanda J. Fairchild (Amanda.Fairchild[at]asu.edu)

Time: TBA

Abstract: The purpose of the course is to cover the substantive rationale for mediation analysis and to present statistical methods for assessing mediating variables. The course will focus on integrating conceptual understanding of the models with statistical methods for their estimation. Cross-sectional and longitudinal models for mediation are examined, and course content is applied in both the SAS and Mplus software packages. Effect size measures for mediation models are also discussed and several substantive examples are evaluated throughout the course.

Prerequisites: Consent of instructor is required to enroll in the course. Typically both graduate level ANOVA and Regression courses are minimum requirements for the course. Structural Equation Modeling experience is desirable.

Spring 2009 (Planned)

PSYC 710, Quantitative Methods for Behavioral Data II

Instructor: M. Lee Van Horn (vanhorn[at]sc.edu)

Time: TBA

Abstract: This is the second course in a graduate level sequence meant to provide Ph.D. students in psychology with the skills to be effective consumers and users of statistics. The second course completes more advanced applications of the GLM model such as higher order factorial ANOVAs, repeated measures ANOVA, and random effects models. This course also aims to provide an overview of some other key issues common to much research in psychology including the presence of missing data, multilevel designs, and the estimation of power.

Prerequisites: Because of space limitations this course sequence is typically only open to graduate students in the Department of Psychology.

STAT 778, Item Response Theory

Instructor: Brian Habing (habing[at]stat.sc.edu)

Abstract: Upon completion of the course the students will be familiar with the major concepts and theoretical issues in item response theory. They will possess the needed technical knowledge to directly consult the more applied research journals in the field at the level expected of a practitioner. They will have the background to continue their studies in a reading course preparing them to utilize the more theoretical journals in the field and to conduct research.

Prerequisites: EDRM 711 or PSYC 710 or STAT 701 or STAT 704.

PSYC 888, Longitudinal Models in Behavioral Science

Instructor: Patrick S. Malone, Malone[at]sc.edu

Time: TBA

Abstract: This course will cover contemporary methods for analyzing data collected from the same respondents over time, with a particular focus on longitudinal panel data. In addition to establishing skill in various specific methods, an emphasis will be placed on identifying and tailoring the models to the particular data and research question. Methods covered will include multilevel models, latent trajectory models, autoregressive models, survival analysis, latent transition analysis, and combinations of the above.

Prerequisites: PSYC 710 or equivalent.

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