Provides instruction in the art and science of writing successful anthropological Ph.D. research proposals. Students will learn how to transform their research ideas and create a viable and fundable research proposal.

Applications of item response theory (IRT) to practical testing problems, including test equating, differential item functioning, computerized adaptive testing, and test construction. Dichotomous and polytomous item response theory models with strong emphasis on computer applications.

Principles and quantitative methods for the analysis of ecotoxicological data.

Topics and research problems in urban geography. Topics may vary.

Training during the third year of a residency for graduate veterinarians desiring specialization in Clinical Microbiology.

Theories, concepts, and techniques for the development, implementation, coordination, and evaluation of rehabilitation and training programs in kinesiology related fields.

Conditional expectation, Brownian motion, semimartingales, stochastic calculus, stochastic differential equations, stochastic control, stochastic filtering.

Introduces topics related to protein and macromolecular structure and function in the context of Microbiology. Course is updated to keep pace with the current research literature.

Public policy implementation literature with emphasis given to the major substantive and methodological issues driving this emerging field of public policy analysis. Bureaucracy's role in policy process, implementation analysis, and theories and methods for studying policy implementation.

Major topics in the philosophy of religion, such as the nature and existence of God, the problem of evil, and the character of religious discourse.

Simultaneous equations and confirmatory factor methods to evaluate structural and measurement models. Emphasis on the interplay between theory and the construction and evaluation of empirical models.

Extensions of classical and generalized linear models with emphasis on longitudinal data analysis. Course will focus on linear mixed models, and marginal and mixed-effect versions of generalized linear models for longitudinal discrete data. Emphasis will be placed on the application of these models to analyze real data.