activity
20102025
most citedFunctional Analysis of Variance for Association Studies

29 citations · 63 across the 8 of their papers we have counts for

collaborators

9 papers

stat.AP2025★ 29 cited

Functional Analysis of Variance for Association Studies

Olga A. Vsevolozhskaya, Dmitri V. Zaykin, Mark C. Greenwood +2

While progress has been made in identifying common genetic variants associated with human diseases, for most of common complex diseases, the identified genetic variants only accoun…

stat.ME2020

A new measure for the analysis of epidemiological associations: Cannabis use disorder examples

Olga A. Vsevolozhskaya, Karl C. Alcover, James C. Anthony +1

Analyses of population-based surveys are instrumental to research on prevention and treatment of mental and substance use disorders. Population-based data provides descriptive char…

q-bio.GN2019★ 17 cited

DOT: Gene-set analysis by combining decorrelated association statistics

Olga A Vsevolozhskaya, Min Shi, Fengjiao Hu +1

Historically, the majority of statistical association methods have been designed assuming availability of SNP-level information. However, modern genetic and sequencing data present…

stat.ME2018

Put the odds on your side: a new measure for epidemiological associations

Olga A Vsevolozhskaya, Dmitri V Zaykin

The odds ratio (OR) is a measure of effect size commonly used in observational research. OR reflects statistical association between a binary outcome, such as the presence of a hea…

stat.ME2018

Maximum value of the standardized log of odds ratio and celestial mechanics

Olga A. Vsevolozhskaya, Gabriel Ruiz, Dmitri V. Zaykin

The odds ratio (OR) is a widely used measure of the effect size in observational research. ORs reflect statistical association between a binary outcome, such as the presence of a h…

stat.ME2018

Detecting weak signals by combining small P-values in genetic association studies

Olga A. Vsevolozhskaya, Fengjiao Hu, Dmitri V. Zaykin

We approach the problem of combining top-ranking association statistics or P-value from a new perspective which leads to a remarkably simple and powerful method. Statistical method…

q-bio.GN2016

Assessment of P-value variability in the current replicability crisis

Olga A. Vsevolozhskaya, Gabriel Ruiz, Dmitri V. Zaykin

Increased availability of data and accessibility of computational tools in recent years have created unprecedented opportunities for scientific research driven by statistical analy…

q-bio.GN2016

The more you test, the more you find: Smallest P-values become increasingly enriched with real findings as more tests are conducted

Olga A. Vsevolozhskaya, Chia-Ling Kuo, Gabriel Ruiz +2

Increasing accessibility of data to researchers makes it possible to conduct massive amounts of statistical testing. Rather than follow a carefully crafted set of scientific hypoth…

stat.ME2010★ 17 cited

Robust Tests in Genome-Wide Scans under Incomplete Linkage Disequilibrium

Gang Zheng, Jungnam Joo, Dmitri Zaykin +2

Under complete linkage disequilibrium (LD), robust tests often have greater power than Pearson's chi-square test and trend tests for the analysis of case-control genetic associatio…