Quran Wu

Developed joint model for longitudinal and survival analysis in palliative studies (submitted to Biostatistics). Develop mediation analysis model with zero-inflated beta mediator and applied to microbiome analysis (published on Genes). Extended the mediation model into mixed zero-inflated beta mediator. Developed R package “IFAA” for robust inference of absolute abundance in microbiome analysis and posted on CRAN (https://cran.r-project.org/web/packages/IFAA/index.html). Extended “IFAA” by including inverse probability weighting to account for false zeros. Collaborated on biomedical projects and working as biostatistician.

Worked on two separate projects: standard error computation adjusting for stratification factors; historical borrowing with elastic prior approach on time series negative binomial endpoints. Reviewed FDA guidance and the existing literatures on both projects. Accessed properties of standard error computation adjustments under variates of conditions based on simulations, to provide further recommendations on future clinical trial projects when stratification factors are involved. Applied elastic prior approach on time series negative binomial endpoints and coded in R. Visualized performance of elastic prior in different situations from simulations. Recommended on when and how to use elastic prior approach to improve efficiency in clinical trials. Attended meetings with cross functional teams in the company to better understand how biostatistician worked and collaborated with every function within a clinical trial study. Delivered final presentations on both projects and provided recommendations on when and how to adapt two methods.

Collaborated with PIs, physicians, statisticians, research nurses, and lab technicians on NIH sponsored observational studies on sepsis & trauma. Provided insights on study design, model development, statistical analysis, and paper publication. Co-authored on 3 medical manuscripts. Oversaw the data management and statistical analysis for large database. From collecting and cleaning the raw data, to developing the analysis ready datasets, to conducting statistical models and generating table/figure outputs for publications. Wrote programs, specs, documentations, for data processing and analysis pipeline. Created innovative visualization tools with R Shiny app to help reviewing medical data and results.

Managed database containing more than 400 patients using QDS, Access, RedCap Created monthly team meeting report to review study updates with all the team members Cleaned and prepared clinical research data with more than 1000 observations to facilitate further research and analysis.

Collaborated on multiple projects on data analysis and dataset creation. Cleaned large datasets (more than a million of observations) and created flags to find eligible patients with SAS. Collaborated with clinical research members on datasets quality control, descriptive tables and graphs creation. Conducted data analysis to determine if multiple factors were significant with ANOVA tests and chi-square tests with SAS and R.

Extracted data using iDataFax from original forms and conduct data validation Used SAS to find eligible patients from more than 50 datasets and conducted analysis on diagnosis differences. Created descriptive tables and graphs to display results to supervisors and PIs using SAS. Utilized SAS programming to create receipt for each patient after participating the study according to more than 50 datasets (SQL included).