Skip to main navigation Skip to search Skip to main content

A survey of laboratory and statistical issues related to farmworker exposure studies

  • Dana B. Barr
  • , Doug Landsittel
  • , Marcia Nishioka
  • , Kent Thomas
  • , Brian Curwin
  • , James Raymer
  • , Kirby C. Donnelly
  • , Linda McCauley
  • , P. Barry Ryan
  • Centers for Disease Control and Prevention
  • Battelle
  • United States Environmental Protection Agency
  • National Institute for Occupational Safety and Health
  • RTI International
  • Texas A&M University System
  • University of Pennsylvania
  • Emory University

Research output: Contribution to journal › Article › peer-review

72 Scopus citations

Abstract

Developing internally valid, and perhaps generalizable, farmworker exposure studies is a complex process that involves many statistical and laboratory considerations. Statistics are an integral component of each study beginning with the design stage and continuing to the final data analysis and interpretation. Similarly, data quality plays a significant role in the overall value of the study. Data quality can be derived from several experimental parameters including statistical design of the study and quality of environmental and biological analytical measurements. We discuss statistical and analytic issues that should be addressed in every farmworker study. These issues include study design and sample size determination, analytical methods and quality control and assurance, treatment of missing data or data below the method's limits of detection, and post-hoc analyses of data from multiple studies.

Original languageEnglish
Pages (from-to)961-968
Number of pages8
JournalEnvironmental Health Perspectives
Volume114
Issue number6
DOIs
StatePublished - Jun 2006

Keywords

  • Analytical methodology
  • Biomarkers
  • Laboratory
  • Limit of detection
  • Omics
  • Quality control
  • Sample size
  • Statistics

Fingerprint

Dive into the research topics of 'A survey of laboratory and statistical issues related to farmworker exposure studies'. Together they form a unique fingerprint.

Cite this