I received my Ph.D. in Epidemiology from the University of Michigan, and I am also an SAS Programmer. I am currently a Lead Data Analyst in Medical School. I have a strong background in biostatistics/epidemiology and 17 years of experience using various software packages to analyse large epidemiological, clinical, genetic, and National Inpatient Sample data sets (SAS, SPSS, R and R studio program).

I am well-versed in statistical models and have devised various analysis strategies for various studies and meta-analyses.

Statistical methods used in my research projects include:

• Poisson Regression Model
• GEE (Generalized Estimating Equations)
• Propensity Score Matching (PSM)
• ROC curve, ANOVA, T-test, Nonparametric Statistics (Kruskal-Wallis test and Wilcoxon
• Signed Rank Test), Cohen’s alpha, Pearson’s Correlation Coefficients, Chi-squared test.
• CMS-HCC Risk Adjustment Model (HCC, RxHCC, ESRD)
• Multilevel Logistic Regression Models, and Ordinal Logistic/Logistic Regression Models
• Linear Mixed Models and Linear Regression Models
• Survival Models, Cox Proportional Hazards model, Accelerated Failure Time Modeling,
• Kaplan-Meier Plot)
• Data analysis with weighted data in the survey sample.
• Power Analysis

In addition, I have previously performed statistical analyses on large longitudinal national data sets:

• Health Retirement Research
• National Health and Nutrition Examination Survey (NHANES) (NHANES)
• Healthcare Cost and Utilization Project (HCUP) and National Inpatient Sample (NIS)))
• CMS-HCC Risk Adjustment Model (D) (HCC, RxHCC, ESRD)
• Meta-analysis to efficiently analyse a large database (Genome-Wide Association Studies).

As a data scientist, I am passionate about data analysis and problem solving.