A disattenuated correlation estimate when variables are measured with error: Illustration estimating cross-platform correlations

K. J. Archer, C. I. Dumur, G. S. Taylor, M. D. Chaplin, Anthony Guiseppi-Elie, G. A. Buck, G. Grant, A. Ferreira-Gonzalez, C. T. Garrett

Research output: Contribution to journalArticle

6 Scopus citations

Abstract

Previous cross-platform reproducibility studies have compared consistency of intensities as well as consistency of fold changes across different platforms using Pearson's correlation coefficient. In this study, we propose the use of measurement error models for estimating gene-specific correlations. Additionally, gene-specific reliability estimates are shown to be useful in prioritizing clones for sequence verification rather than selecting clones using a simple random sample. The proposed 'disattenuated' correlation may prove useful in a wide variety of studies when both X and Y are measured with error, such as in confirmation studies of microarray gene expression values, wherein more reliable laboratory assays such as real-time polymerase chain reaction are used.

Original languageEnglish (US)
Pages (from-to)1026-1039
Number of pages14
JournalStatistics in Medicine
Volume27
Issue number7
DOIs
StatePublished - Mar 30 2008

Keywords

  • Correlation
  • Measurement error
  • Microarray
  • Regression calibration

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability

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