The basic statistical methods course applied to the medical and health sciences. Topics include measurement issues, regression models, analysis of variance models (ANOVA), measures of association, categorical data analysis, survival analysis, and advanced topics (Meta Analysis and Bayesian approaches to design and analysis). Techniques for selecting appropriate sample sizes and power are discussed. The use of a computer and SAS is required as a means of performing many of the statistical analyses. Journal articles will be reviewed in teams to put in practice the statistical and design principles that the students have learned. Course objectives are:
- Introduce common advanced statistical methods currently utilized in the medical literature and promote understanding of their appropriate use.
- Familiarize the students with accomplishing computer analyses utilizing the statistical methods so that they can understand and be comfortable reading the literature and interact with professional biostatisticians to accomplish analyses for their own research projects.
Prerequisites: Either of the beginning biostatistics courses (DCS 5391 Mathematical Biostatistics for the Clinical Investigator or DCS 5309 Conceptual Biostatistics for the Clinical Investigator) and Biostatsitics Laboratory I. Enrollment in this course requires concurrent enrollment in Biostatistics Lab II
Credit: 3 hours
Grading Criteria: Pass/Fail based on weekly homework assignments (10%), and two in class exams (45% each)
Semester Offered: Spring
Course Director: Joan S. Reisch, PhD, Professor, Dept of Clinical Sciences, Division of Biostatistics, (E1.401CD), phone: 214 648-2028, fax: 214 648-7673
Course Administrator: Mack Dressler, Assistant Administrator for Education and Degree Programs, The Department of Clinical Sciences, phone: 214 648-2558, fax: 214 648-3934
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