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Course Criteria
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3.00 Credits
This course offers an introduction to the analysis of observed times to events, e.g., times to death (survival times). The course focuses on methods of regression generalized to the case of censored survival data. Regression models studied include non-parametric (Kaplan-Meier), semi-parametric (Cox's PH Model), and parametric regression models (Exponential, Weibull, Log-Logistic, & others). Other topics covered include model development, model adequacy, extensions to the Cox PH model, recurrent event models and frailty models. 3.000 Credit Hours 3.000 Lecture hours Levels: Graduate Semester Schedule Types: Lecture Graduate Studies College Biostatistics Department Course Attributes: Elective Course
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3.00 Credits
This course will address advanced statistical techniques used in the design and analysis of both clinical and sequential trials. 3.000 Credit Hours 3.000 Lecture hours Levels: Graduate Semester Schedule Types: Lecture Graduate Studies College Biostatistics Department Course Attributes: Elective Course
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3.00 Credits
This course is designed for student to gain practical experience in integration of statistical theory and application in current research, systematic formulation of research problems, data formatting, data collection, study design, data analysis, and interpretation and communication of results. 3.000 Credit Hours 3.000 Lecture hours Levels: Graduate Semester Schedule Types: Lecture Graduate Studies College Biostatistics Department
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1.00 - 3.00 Credits
This course is designed to cover special topics in theory and methods of Biostatistics that are not covered in regular courses. The topics will depend on the researchinterests of the instructor and the students. 1.000 TO 3.000 Credit Hours 3.000 Lecture hours Levels: Graduate Semester Schedule Types: Lecture Graduate Studies College Biostatistics Department
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3.00 Credits
This course consists of readings and research in the current biostatistical literature, advaced topics in biostatistical theory and methods, and a supervised research project which will potentially lead to publications and/or presentations. Prerequisites: Permission of instructor 1.000 TO 12.000 Credit Hours 1.000 TO 12.000 Lab hours Levels: Graduate Semester Schedule Types: Independent Study Graduate Studies College Biostatistics Department
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1.00 - 12.00 Credits
Required course for Master of Science students who choose the Non-Thesis Option. Consists of one or more consulting project write-up(s), directed by a Biostatistics faculty member. A formal oral presentation is required at the conclusion of the consulting project(s). 1.000 TO 12.000 Credit Hours 1.000 TO 12.000 Lab hours Levels: Graduate Semester Schedule Types: Internship/Practicum Graduate Studies College Biostatistics Department
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3.00 Credits
The thesis project for the MS program will be for two types: (i) use of established but state-of-the-art statistical tools to analyze and report on collected data sets; or (ii) a rigorous review of statistical literature, possibly involving a small amount of methodological research, that has potential use in complex biomedical data analysis. Prerequisite: Consent of Major Advisor. 3.000 TO 9.000 Credit Hours Levels: Graduate Semester Schedule Types: Thesis Graduate Studies College Biostatistics Department Course Attributes: Elective Course
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3.00 Credits
Fitting of generalized linear models, diagnostics, asymptotic theory, overdispersion, quasi-likelihood, multicategorical responses, estimating equations, generalized linear mixed models. 3.000 Credit Hours 3.000 Lecture hours Levels: Graduate Semester Schedule Types: Lecture Graduate Studies College Biostatistics Department
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3.00 Credits
This course is a study of the general linear statistical model. Topics include the analysis of linear models in univariate data, distributions of quadratic forms, full rank linear models and fixed effect models of less that full rank. Both balanced and unbalanced random and mixed models will also be covered. 3.000 Credit Hours 3.000 Lecture hours Levels: Graduate Semester Schedule Types: Lecture Graduate Studies College Biostatistics Department
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3.00 Credits
Statistical methods for describing variation in qualitative and quantitative (disease) traits, including decomposition of trait variation into components representing genes, enviroment and gene-environment interaction. Topics include transmission of genes in populations, heritability, polygenic and multifactorial traits, complex segregations analysis, methods of mapping and characterizing simple and complex trait loci, pedigree analysis, variance components estimation, likelihood based and Bayesian interval mapping, epistasis, and use of public domain genetic analysis software. 3.000 Credit Hours 3.000 Lecture hours Levels: Graduate Semester Schedule Types: Lecture Graduate Studies College Biostatistics Department
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