Fundamental statistical concepts related to the practice of public health: descriptive statistics; probability; sampling; statistical distributions; estimation; hypothesis testing; chi-square tests; simple and multiple linear regression; one-way ANOVA. . Taught at a more advanced mathematical level than Biostat 503. Use of the computer in statistical analysis.
Concepts and methods for analyzing survival time data obtained from following individuals until occurrence of an event or their loss to follow-up. Survival time models, clinical life tables, survival distributions, mathematical and graphical methods for evaluating goodness of fit, comparison of treatment groups, regression models, proportional hazards models, censoring mechanisms.
Survival Analysis Applied to Epidemiologic and Medical Data
Summer
term(s)
1 Credit Hour(s)
Instructor(s):
Staff; Kalbfleisch, Jack
Prerequisites: Introductory level course in statistics.
The primary goal of this course is to give a general introduction to survival analysis using only elementary mathematics and relying heavily on examples and intuitive explanations. The mathematical level is completely accessible with knowledge of high school algebra, one semester of calculus, and a one-year course in basic statistical methods. With this background, participants should be able to appreciate the methods and apply these methods using standard statistical software. Examples will be chosen from various epidemiological and medical applications. The topics covered will be: an introduction to survival probability models, hazard rates and survivor functions; xponential and Weibull survival models; right censoring and left truncation; life tables and the Kaplan-Meier Estimate; two sample and k sample nonparametric tests; log rank and censored data Wilcoxon tests; parametric methods for analyzing survival data: the Weibull regression model; semi parametric methods: Cox proportional hazard model. The statistical techniques will be illustrated using various medical and epidemiological studies. Students will be challenged with some applied (non-computer) problems to illustrate the main ideas of survival analysis and to solidify the concepts. There will also be a number of exercises that will utilize computer software to analyze data. Prerequisite: Introductory level course in statistics including an introduction to regression methods.
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