1 - 4 of 4 results for: MED 262

The course will focus on computational approaches to ensure that all data, code, and analyses can be captured in a reproducible workflow, to be confirmed and replicated by you in the future, by other members of your team, and by reviewers and other researchers. We will cover how to satisfy FAIR principles, version control, how to create a git repository, utilize Github and how to create a reproducible dataset. Prerequisites: Basic knowledge of R. Recommended (not required): EPI 202 or 261/262, STATS 60, or MS&E 125.

This 3-week mini-course will dive into the biology of non-model organisms, and the approaches we can use to study them. Traditionally in Biology, model organisms have been used to answer new questions. Yet, studying a more diverse array of organisms can lead to new discoveries. We will explore the world of non-model Biology through a series of short lectures, primary literature discussions, talks from experts working on non-model organisms, and some practical sessions including a field sampling. No prerequisites required.

Methods for analyzing longitudinal data. Topics include Kaplan-Meier methods, Cox regression, hazard ratios, time-dependent variables, longitudinal data structures, profile plots, missing data, modeling change, MANOVA, repeated-measures ANOVA, GEE, and mixed models. Emphasis is on practical applications. Prerequisites: basic ANOVA and linear regression.