J Prev Med Public Health.  2007 Mar;40(2):108-113. 10.3961/jpmph.2007.40.2.108.

Statistical Issues in Genomic Cohort Studies

Affiliations
  • 1Cancer Biostatistics Branch, Division of Cancer Registration and Epidemiology, National Cancer Center, Korea. shpark@ncc.re.kr

Abstract

When conducting large-scale cohort studies, numerous statistical issues arise from the range of study design, data collection, data analysis and interpretation. In genomic cohort studies, these statistical problems become more complicated, which need to be carefully dealt with. Rapid technical advances in genomic studies produce enormous amount of data to be analyzed and traditional statistical methods are no longer sufficient to handle these data. In this paper, we reviewed several important statistical issues that occur frequently in large-scale genomic cohort studies, including measurement error and its relevant correction methods, cost-efficient design strategy for main cohort and validation studies, inflated Type I error, gene-gene and gene-environment interaction and time-varying hazard ratios. It is very important to employ appropriate statistical methods in order to make the best use of valuable cohort data and produce valid and reliable study results.

Keyword

Cohort studies; Epidemiologic methods; Validation studies; Research design; Measurement error; Gene-environment interaction; Proportional hazards models; Genomics

MeSH Terms

Research Design
Reproducibility of Results
Proportional Hazards Models
Humans
*Human Genome Project
*Data Interpretation, Statistical
Cost-Benefit Analysis
*Cohort Studies
Full Text Links
  • JPMPH
Actions
Cited
CITED
export Copy
Close
Share
  • Twitter
  • Facebook
Similar articles
Copyright © 2024 by Korean Association of Medical Journal Editors. All rights reserved.     E-mail: koreamed@kamje.or.kr