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5160.0: Wednesday, November 10, 2004: 2:30 PM-4:00 PM | |||
Oral | |||
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During this session, attendees will be presented with a variety of methodological approaches to quantitative epidemiology, including Bayesian evaluation of the timeliness of outbreak detection, a strategy for partitioning a population attributable fraction in a multiple risk factor model, and using multiple imputation strategies for including data sets with missing values in multivariate analyses. Making information from large public data files more useful for people without sophisticated statistical knowledge or software will also be presented. | |||
Learning Objectives: At the conclusion of the session, the participant (learner) in this session will be able to: 1. List methods for evaluating outbreak detection algorithms in surveillance systems. 2. Understand the limitations and issues of estimating a population attributable fraction in multiple risk factor models. 3. Understand and receive access to a workbook for manipulating large vital statistics data sets to produce data for community health assessments. 4. Identify an alternative method to retain records with missing values for use in multivariate analyses. | |||
A Bayesian approach to evaluating timeliness of outbreak detection in surveillance David L Buckeridge, MD, MSc, Paul Switzer, PhD, Mark A Musen, MD, PhD | |||
Partitioning a population attributable fraction in a model with sequential effects Craig A. Mason, PhD, Shihfen Tu, PhD | |||
A workbook for manipulating state vital statistics data to describe mortality and disparity trends at the local level Christopher J. Mansfield, PhD, Denise Kirk, MS, James L. Wilson, PhD, Luke Schwankl, BA, Michael L. Gwaltney, BA, Zoe Yetman, BSBA | |||
Using multiple imputation as a strategy for including data sets with missing values in multivariate analyses Myrna R. Epstein, PhD, MPH, Mitchell Watnik, PhD | |||
See individual abstracts for presenting author's disclosure statement and author's information. | |||
Organized by: | Epidemiology | ||
Endorsed by: | Statistics | ||
CE Credits: | CME, Health Education (CHES), Nursing |