Events

episummer Introduction to Biostatistics Course Description The course will give an overview of the basic tools for the collection, analysis, and presentation of data in all areas of public health. The topics covered will include descriptive statistics; hypothesis testing; methods for comparison of discrete and continuous data including ANOVA, t-test, correlation, chi-squared analysis, linear and logistic regression, and non-parametric approaches. This course will provide a foundation for the skill-building courses and focused epidemiologic courses.  

episummer Introduction to Meta-Analysis   Course Description Meta-Analysis is the process of synthesizing data from multiple studies to yield a more complete understanding of the effect. It is the core of evidence-based medicine and epidemiology. The goal of this course is to teach students how to perform a meta-analysis, to interpret the results properly, and to present the results in a manner that is clear and intuitive. The techniques that we discuss in these workshops are relevant to any field where a meta-analysis might be employed. Participants typically work in such fields as medicine, epidemiology, health sciences, biostatistics, nursing, veterinary medicine, psychology, education, criminal justice, ecology, marketing, among others. Basic course (20 hours) June 1-15 In the basic course we explain how to conduct and report the results for a meta-analysis. In an analysis where the effect size is consistent across studies the goal will be to identify that common effect size and consider the clinical implications of the findings. In an analysis where the effect size varies across studies the goal will be to identify the mean effect size and also to quantify the variation in effects and consider the clinical implications of this variation: Is it the case that the treatment's effect varies from moderate to large; or from minor to moderate; or is the treatment helpful in some cases but harmful in others?

episummer Introduction to Multi-Level Modeling   Course Description This course will provide an overview of the theory underlying the use of multi-level models, using a parametric framework, as well as teach the basic application of methods necessary to conduct and interpret multi-level analyses of epidemiologic data. After reviewing basic statistical and theoretical principles of linear and logistic regression models using only one level of organization, lecture and lab sessions will be focused on the use of random-effects models and generalized estimating equation (GEE) models for the analysis of data with two levels. Hands-on exercises will use data from an investigation of the influence of NYC neighborhoods on obesity, focusing on the application and interpretation of regression models that account for clustered observations and group-level covariates. STATA code will be provided for all exercises and participants will learn how to implement multi-level models. R and SAS code will also be provided.

episummer Successful Scientific Writing Course Description This course takes an active, participatory approach to learning how to communicate the findings of scientific research more effectively in writing to expedite the publication of peer-reviewed manuscripts. Over the course of four weeks, registrants will engage in problem solving and practical application of scientific writing skills. Specifically, registrants will critique actual published and unpublished manuscripts and complete a range of exercises that exemplify the real-world challenges that authors face. No prerequisites required.