Biostatistics and Epidemiology Course Descriptions
Introduction to Biostatistics
This course provides a detailed introduction to the theory and application of statistical techniques that are commonly used in clinical research. Topics include: probability distribution, hypothesis testing, confidence intervals, sample size and power calculations, measures of association, t-tests, nonparametric analysis, and analysis of variance. By the end of the course, students should be able to conduct all of the basic statistical tests and recognize the assumptions behind their analyses.
Stata is a powerful and yet easy to use statistical package that runs on Windows, Macintosh and UNIX platforms. This class is designed for people who are just getting started with statistical computing and intend on taking few statistics courses. The students in the class will have a hands-on experience using Stata for data management, statistical graphics, and statistical analysis.
Stata software will be made available to all students. Students will be expected to bring their laptop to the workshop.
This course introduces students involved in clinical research to the practical application of regression analyses. Linear regression, logistic regression, Cox proportional hazards survival models, generalized estimating equations and multilevel regression modeling will be covered, and examples from fields of medicine will be chosen for illustration. Students will be introduced to the general concepts in model selection, goodness-of-fit, and testing procedures. Each lecture is accompanied by a data analysis using Stata and a classroom discussion of the results. Upon completion of the course, students should be able to carry out all five kinds of regression analyses for their own projects.
This course introduces students involved in clinical research to the distinction between randomized clinical trials and observational study. It discusses the statistical background for causal inference and teaches statistical methods such as propensity score analysis and instrumental variable analysis for drawing the best possible inference from observational studies. Published literature utilizing large secondary databases such as NHANES and SEER-Medicare are discussed to motivate future studies that can be planned. Steps for systematic literature review and various methodologies for meta-analysis will be taught.
At the end of the course, students should be able to rigorously design and write data analysis plans for observational studies. They should also be able to analyze data (using Stata) for summarizing epidemiological studies, for using multiple regression analyses (linear, logistic, and survival), to adjust for confounders, and for performing propensity score analysis and meta-analysis.
The goal of the Collaborative Program in Nutrition and Cancer Prevention (PNCP) is to provide opportunities for multidisciplinary training in laboratory and clinical research in the basic sciences of cell biology, metabolism, immunology, and cancer biology, in addition to nutritional sciences, epidemiology, and research methodology for postdoctoral (MD and PhD) fellows, in order to prepare them for careers as independent investigators in the field of nutrition and cancer prevention. The proposed program will address a major need to support career development for applicants who are qualified in diverse areas such as oncology, cell biology, gastroenterology, metabolism, or nutrition, and require intensive and individualized training to develop their research goals and careers in nutrition and cancer prevention.
This course introduces students to basics principles of biostatistics and epidemiology.
This course introduces the Physician Assistant student to the concepts of basic statistical methods used in health care research. Topics include population sampling, graphical presentation of data, frequency distributions, measures of central tendency and dispersion, one-sample and two-sample inference (hypothesis testing), interval estimation (confidence intervals), analysis of variance, chi-square test, applications of sample size and statistical power, correlation and linear regression, survival analysis and Cox multivariate regression. Students will be introduced to the statistical software program STATA 9.0. Homework assignments and take-home final examination will emphasize the use of this software for application to the Research I and II courses required in the Physician Assistant program.
This course introduces the Physician Assistant student to the fundamental concepts of epidemiology. After completion of the course, the student should be able to apply those fundamentals in evaluating medical research, including the assessment of the validity of data and a methodological critique of current research as it relates to the practice of medicine. The course is specifically designed to address the following three objectives: 1) to introduce the Physician Assistant student to the fundamental measures of disease occurrence, such as incidence, prevalence, rate, risk, etc., and to illustrate their use in the public health arena; 2) to provide an introduction to the major types of epidemiological study designs used in clinical research: descriptive (cross-sectional/correlational), observational (cohort, case-control), and experimental (clinical trial, community trial); and 3) to expose the Physician Assistant student to current literature in epidemiology with an emphasis on interpreting the information presented and critiquing methodology.