Core biostatisticians at Center for Preventive Ophthalmology and Biostatistics are available to support consultation and collaboration in biostatistics and epidemiology for Penn vision scientists. Biostatisticians provide advice on study design, sample size/power determination, data management, data analysis, data interpretation, and data presentation. They are also available to help with development and writing of grant applications and manuscripts.

To initiate a project, contact Dr. Gui-Shuang Ying: gsying@pennmedicine.upenn.edu

Core biostatisticians have extensive experience in handling designs that are typical of vision research. For example, in ophthalmologic and vision research data are often collected from both eyes of a subject (a patient or an animal), ERG is often measured in both eyes of a dog, visual acuity and OCT are often measured in both eyes of a patient with age-related macular degeneration. The data collected from two eyes of a subject are usually correlated, thus cannot be analyzed using the standard statistical methods for independent data. Core biostatisticians are very experienced in analyzing such correlated eye data. See the following tutorial papers led by Core biostatisticians on the analysis of correlated eye data.

Ying GS, Maguire MG, Glynn RJ, Rosner B. Calculating Sensitivity, Specificity, and Predictive Values for Correlated Eye Data. Invest Ophthalmol Vis Sci. 2020 Sep 1;61(11):29. doi: 10.1167/iovs.61.11.29.

Ying GS, Maguire MG, Glynn RJ, Rosner B. Tutorial on Biostatistics: Longitudinal Analysis of Correlated Continuous Eye Data. Ophthalmic Epidemiol. 2020 Aug 2:1-18. doi: 10.1080/09286586.2020.1786590.

Ying GS, Maguire MG, Glynn R, Rosner B. Tutorial on Biostatistics: Statistical Analysis for Correlated Binary Eye Data. Ophthalmic Epidemiol. 2018 Feb;25(1):1-12. doi: 10.1080/09286586.2017.1320413.

Ying GS, Maguire MG, Glynn R, Rosner B. Tutorial on Biostatistics: Linear Regression Analysis of Continuous Correlated Eye Data. Ophthalmic Epidemiol. 2017 Apr;24(2):130-140. doi: 10.1080/09286586.2016.1259636.

 

Click here to read the guidelines for Excel files to be used for data analysis