ArticleOphthalmology science2026
Evaluation of Statistical Methods for Clustered Eye Data with Skewed Distribution.
Article in Ophthalmology science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Purpose: To evaluate the performance of various analysis approaches for skewed correlated eye data from 2 eyes of a subject in the same comparison group, which is common in ophthalmology and vision research. Design: Simulation study and real data analysis. Subjects: Simulated subjects and participants of the Dry Eye Assessment and Management (DREAM) study. Methods: We simulated skewed correlated data using (skewness, kurtosis) = (27, 50) and (0.06, 5.9), intereye correlation ( Main Outcome Measures: Type 1 error rate and statistical power. Results: Conclusions: When comparing skewed correlated eye measures between 2 groups of subjects with their 2 eyes in the same comparison group, clustered Wilcoxon methods can be used. Alternatively, skewed data can be normalized before applying GEE score or LMM, which may achieve slightly higher statistical power than clustered Wilcoxon methods and offers flexibility to adjust for other covariates. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.