Systematic Statistical Analysis of Microbial Data from Dilution Series

J. Andrés Christen () and Albert E. Parker ()
Additional contact information
J. Andrés Christen: Centro de Investigación en Matemáticas (CIMAT-CONACYT)
Albert E. Parker: Montana State University

Journal of Agricultural, Biological and Environmental Statistics, 2020, vol. 25, issue 3, No 4, 339-364

Abstract: Abstract In microbial studies, samples are often treated under different experimental conditions and then tested for microbial survival. A technique, dating back to the 1880s, consists of diluting the samples several times and incubating each dilution to verify the existence of microbial colony-forming units or CFU’s, seen by the naked eye. The main problem in the dilution series data analysis is the uncertainty quantification of the simple point estimate of the original number of CFU’s in the sample (i.e., at dilution zero). Common approaches such as log-normal or Poisson models do not seem to handle well extreme cases with low or high counts, among other issues. We build a novel binomial model, based on the actual design of the experimental procedure including the dilution series. For repetitions, we construct a hierarchical model for experimental results from a single laboratory and in turn a higher hierarchy for inter-laboratory analyses. Results seem promising, with a systematic treatment of all data cases, including zeros, censored data, repetitions, intra- and inter-laboratory studies. Using a Bayesian approach, a robust and efficient MCMC method is used to analyze several real data sets.

Keywords: Dilution experiments; Binomial likelihood; Bayesian inference; Hierarchical models; MCMC (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s13253-020-00397-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jagbes:v:25:y:2020:i:3:d:10.1007_s13253-020-00397-0

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/13253

DOI: 10.1007/s13253-020-00397-0

Access Statistics for this article

Journal of Agricultural, Biological and Environmental Statistics is currently edited by Stephen Buckland

More articles in Journal of Agricultural, Biological and Environmental Statistics from Springer, The International Biometric Society, American Statistical Association
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().