Reliability of environmental sampling culture results using the negative binomial intraclass correlation coefficient

Sharif S Aly, Jianyang Zhao, Ben Li, Jiming Jiang

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

The Intraclass Correlation Coefficient (ICC) is commonly used to estimate the similarity between quantitative measures obtained from different sources. Overdispersed data is traditionally transformed so that linear mixed model (LMM) based ICC can be estimated. A common transformation used is the natural logarithm. The reliability of environmental sampling of fecal slurry on freestall pens has been estimated for Mycobacterium avium subsp. paratuberculosis using the natural logarithm transformed culture results. Recently, the negative binomial ICC was defined based on a generalized linear mixed model for negative binomial distributed data. The current study reports on the negative binomial ICC estimate which includes fixed effects using culture results of environmental samples. Simulations using a wide variety of inputs and negative binomial distribution parameters (r; p) showed better performance of the new negative binomial ICC compared to the ICC based on LMM even when negative binomial data was logarithm, and square root transformed. A second comparison that targeted a wider range of ICC values showed that the mean of estimated ICC closely approximated the true ICC.

Original languageEnglish (US)
Pages (from-to)1-7
Number of pages7
JournalSpringerPlus
Volume3
Issue number1
DOIs
StatePublished - 2014

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sampling
slurry
simulation

Keywords

  • Generalized linear mixed model
  • Intraclass correlation coefficient
  • Negative binomial mixed model
  • Variance components

ASJC Scopus subject areas

  • General

Cite this

Reliability of environmental sampling culture results using the negative binomial intraclass correlation coefficient. / Aly, Sharif S; Zhao, Jianyang; Li, Ben; Jiang, Jiming.

In: SpringerPlus, Vol. 3, No. 1, 2014, p. 1-7.

Research output: Contribution to journalArticle

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