Biostatistician II

• Manage the statistical needs of the Department of Ophthalmology and Vision Science in collaboration with program investigators. Develop objectives, design sampling, randomization, and create data collection procedures using the latest data analysis and visualization techniques.
• Perform power/sample size analysis and develops plans for study monitoring and statistical analysis.
• Oversee data collection, database maintenance, assessment of various data bases and sources, and interpretation of data analysis results. Collaborate, advise, and assist investigators in designing and determining the appropriate statistical methodology to meet their study needs and objectives.
• Use various modern statistical methods and mathematical software packages to summarize, interpret, and communicate statistical results.
• Design, implement, and coordinate study activities and process improvements.
• Advise investigators in determining the appropriate statistical methodology to meet their study needs and objectives. Recommend process improvements.
• Develop and maintain databases using various statistical software packages, write statistical computer programs, and review and summarize analysis results.
• Evaluate sources of existing data in order to determine any limitations in terms of reliability, usability, and generalizability.
• Provide expertise consultation, technical assistance, and coordination for a wide variety of investigators, students, and other research faculty. 
• Prepare statistical sections for applications, grant proposals, presentations, and publications including designing tables, visual representations, and reports for specific research studies.
• Serve as primary representative for the analysis and presentation of data to all stakeholders.

Knowledge, Skills and Abilities:

• Sample size calculations for a spectrum of basic and clinical projects.
• Writing statistical analysis plans.
• Database creation and maintenance.
• Performing statistical analyses in SAS and other programs.
• Both parametric and non-parametric statistical methods.
• Measures of agreement eg ICCs, Limits of agreement, Bland-Altman plots.
• Multivariable regression analyses and dealing with confounding. 
• Dealing with multiplicity eg False discover rate methods.