Home > MI255-W: Exposure-Response Modeling of Categorical, Count and Time-To-Event Data Using Bayesian and Maximum Likelihood Methods (2 CR)
MI255-W: Exposure-Response Modeling of Categorical, Count and Time-To-Event Data Using Bayesian and Maximum Likelihood Methods (2 CR)
Product Description
Spring 2011
MI255 is an intensive course providing an introduction to modeling of categorical, count, and time-to-event data, and the practical use of WinBUGS and NONMEM® for such applications. The course provides some basic theory and illustrates some of the advantages of using Bayesian methods for these types of data sets. Participants may apply the 2 credit hours from this course to the Metrum Institute Certificate Program in Pharmacometrics.
Prerequisites: Experience with PK-PD modeling and some familiarity with nonlinear regression, mixed-effects modeling and R (or S-Plus) is required. Prior experience with Bayesian modeling using WinBUGS is required. Applicable MI courses include: MI200, MI205 (formerly MI220), MI210, MI212 and MI250, or
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Computer Hardware/Software: This course requires a Windows computer with an available USB 2.0 port. All required software used for hands-on examples will be freeware/open-source software and simple instructions will be provided for users to configure their computers before the course.