BIO Spring 2 Courses

BIO9000 Capstone III MS Biostatistics

Credits: 1 Offered: Spring 2

The Capstone is a required three-semester course for students in the MS in Biostatistics Program. It provides experience in the art of consulting and in the proper application of statistical techniques to clinical and translational research. Students will bring together the skills they have acquired in previous coursework and apply them to the consulting experience. Learning will take place by doing.

In the Fall term, the capstone-related lectures and project will engage students in important discourse regarding data management and research ethics.

In the Spring I term, the capstone-related lectures and project will challenge students to operationalize conceptual research questions into testable hypotheses. Additionally students will demonstrate their ability to determine the appropriate analytic method to test their hypotheses and discuss analytic alternatives when important statistical assumptions are violated.

In the Spring II term, students will meet the capstone requirements by shadowing Biostatistics faculty in the Center for Biostatistics consultation service. By shadowing the Biostatistics faculty, students will learn how to: 1) successfully collaborate with non-statisticians (primarily clinical faculty) at the Icahn School of Medicine at Mount Sinai, 2) provide appropriate study design-related and methodologic approaches to cutting edge research questions, 3) successfully conduct advanced preliminary analyses, and 4) communicate their findings to an institution-wide audience at an MS in Biostatistics capstone symposium at the end of the Spring II term.

BIO9001 Applied Analysis of Healthcare Databases

Credits: 3 Offered: Spring 2

Applied Analysis of Healthcare Databases provides a comprehensive overview of healthcare databases that are commonly used for research. The overall course objective is to provide students with working knowledge of available healthcare databases, research questions that can be addressed using these databases and methods used for analysis of large scale databases. This course will prepare students to identify and use national and local healthcare databases in their own research. Students will evaluate published database studies, complete programming exercises with SAS statistical software and hands-on access to a large database, and prepare a proposal for analyzing a specific research question using a large healthcare database.

Pre-Requisites: (BIO6400 or MPH0300) AND (BIO6100 or MPH0400)

BIO9100 Survival Analysis

Credits: 3 Offered: Spring 2

The aim of this course is to provide a systematic training in both the theoretical foundations and the model building strategies of longitudinal analysis for MS/MPH and PhD students who have already had some data analysis experience. The course presents modern approaches to the analysis of longitudinal data with topics that include linear mixed effects models, generalized linear models for correlated data (including generalized estimating equations), computational issues in using these methods, and missing data assumptions and methods.e

Prerequisites: -BIO6400, BIO6500, BIO8500, and BIO8700

BIO9200 Analysis of Longitudinal Data

Credits: 3 Offered: Spring 2

The aim of this course is to provide a systematic training in both the theoretical foundations and the model building strategies of linear regression models for students who have already had some data analysis experience. The course presents modern approaches to the analysis of longitudinal data. Topics include linear mixed effects models, generalized linear models for correlated data (including generalized estimating equations), computational issues and methods for fitting models, and dropout or other missing data.

Prerequisites: BIO6400, BIO6500, BIO8500, and BIO8700 -Intermediate programming proficiency in R