# Unified group sequential designs for clustered data (eye level) in randomized eye trials > **NIH NIH R21** · GEORGE WASHINGTON UNIVERSITY · 2022 · $210,803 ## Abstract ABSTRACT Interim data monitoring is essential to the successful design, conduct, and reporting of long-term randomized clinical trials for eye diseases. Group sequential methods are the most commonly used methods for studies with interim monitoring plans, which control type I error rate, protect statistical power, and avoid false positive/negative findings. However, when both eyes (clustered) from a patient are included in a study, group sequential methods accounting for the inter-eye correlation to the best of our knowledge, essentially do not exist for all design options (different ways of randomizing both eyes or one eye of a patient) in the literature. In this application, through a collaborative effort between George Washington University and Wills Eye Hospital, that combines theoretical and applied statistical expertise, we propose to develop and evaluate a unified group sequential design for vision research that accommodates all possible design options while accounting for inter-eye correlations when both eyes of a patient are included in the study. These design options include: 1) only one eye eligible and randomized per person; 2) paired eye design; 3) paired eye design plus cases contributing one eye only; 4) both eyes on the same study arm (clustered) plus cases contributing one eye only; and 5) two eyes either on the same or different arms plus cases contributing one eye only - unified design, which includes the first four designs as special cases. The proposed project aims to achieve the following specific aims: 1) to propose, investigate and evaluate design properties for group sequential trials with clustered (eye level) continuous endpoints; 2) to propose, investigate and evaluate design properties for group sequential trials with clustered (eye level) binary endpoints; and 3) to propose, investigate and evaluate design properties for group sequential trials with clustered (eye level) survival endpoints. Completion of these proposed aims will provide investigators with a new suite of statistical tools to improve the design and monitoring of long-term trials and minimize the likelihood of making interim decisions that might lead to unnecessary study continuation or early stopping. Each specific aim will be achieved through the following steps: 1) rigorously establish the theoretical properties of the proposed methodology; 2) examine the finite-sample performance through extensive simulation studies; and 3) apply the proposed methods to interim data from real example eye trials (the Age-Related Eye Disease Study, the HOme Monitoring of the Eye Study, the Cryotherapy for Retinopathy of Prematurity Trial, and the Early Treatment for Retinopathy of Prematurity Study) to demonstrate the usefulness of the proposed methods. Computer programs implementing the new methodology will be made available through an R Shiny App with a web interface for practitioners' easy access and convenient use. Detailed usage guides and documentation will be provide... ## Key facts - **NIH application ID:** 10527031 - **Project number:** 1R21EY032951-01A1 - **Recipient organization:** GEORGE WASHINGTON UNIVERSITY - **Principal Investigator:** Guoqing Diao - **Activity code:** R21 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $210,803 - **Award type:** 1 - **Project period:** 2022-09-01 → 2024-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10527031 ## Citation > US National Institutes of Health, RePORTER application 10527031, Unified group sequential designs for clustered data (eye level) in randomized eye trials (1R21EY032951-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10527031. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*