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Expert's teaching courses include Chronic Disease Epidemiology, Survey Sampling, Applied Linear Models for Public Health, Environmental Health, Epidemiology, and Biostatistics. Her research interests include children’s health with a focus on pediatric asthma (prevalence, clinical management, environmental triggers and academic outcomes among school aged children), chronic disease, health disparities and disease surveillance. Future coursework will include development in the areas of Biostatistics and Epidemiology.

Her duties, while working as a Chronic Disease Epidemiologist, included identifying and analyzing chronic disease data, conducting disease surveillance, and providing evidence and guidance for disease control measures at the state and local levels. Biostatistical analysis and programming of data was required for the evaluation of chronic disease burden and the compilation of health status data both internally and for dissemination to public health partners. These measures include disease prevalence, incidence, morbidity and mortality rates as requested internally and by various healthcare partners and community members. She has extensive experience with statistical software including SAS 9.1 for Windows.

Expert has worked as a biomathematician, evaluating data for Antimicrobial Susceptibility Testing and antifungal development for QC/Manufacturing. The minimal inhibitory concentration of each bacterial strain against several antimicrobials was determined for use in the clinical field. She developed and implemented mathematical techniques to enhance biomedical company resources, providing statistical support and performing data analyses for all functional areas of the company along with understanding of Good Manufacturing Practice (GMP). Involved SAS programming (Macros, SQL) in a UNIX environment in which data extraction and manipulation from Oracle into the mainframe system was integral Communication of statistical principles, assumptions, and implications was required across departments such as QC, Manufacturing, Engineering and Biosciences.

Experience with applied health statistics including nonparametric and parametric statistics - survival data analysis, logistic regression models, epidemiology and study design including power analysis, clinical trials data and programming, general linear models, analysis of complex stratified data, weighted data

Species classification using discriminant function analysis and binary logistic regression. Survival analysis with time dependent covariates for unmarried mothers national cohort. Survey regression with disproportionate stratified data from the BRFSS. Non-parametric analysis for ranked differences of BMI by race.