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dc.contributor.authorDeVries, Todd Alan
dc.contributor.authorHamilton, Martin A.
dc.date.accessioned2017-10-31T20:56:38Z
dc.date.available2017-10-31T20:56:38Z
dc.date.issued1999
dc.identifier.citationDeVries, T., M. Hamilton."Estimating the Antimicrobial Log Reduction: Part 1. Quantitative Assays," Quantitative Microbiology, 1:29-45 (1999).en_US
dc.identifier.issn1388-3593
dc.identifier.urihttps://scholarworks.montana.edu/xmlui/handle/1/13905
dc.description.abstractIn quantitative antimicrobial assays, the responses are counts of viable microbes in two treatment groups. One group is treated with a chemical germicide and the other group is control, treated with an inactive chemical. This is part 1 of a pair of papers that pertain to assays that estimate the log reduction (LR), in the density of viable microbes, attributable to the germicide treatment (part 2 is concerned with presence=absence responses). Such assays are used by producers, consumers, and regulatory agencies to assess the ef®cacy of liquid germicides. We de®ne and compare the two different mathematical formulations for LR that are commonly used in practice when there are replicate density measurements. One LR parameter is based on the mean of the log-transformed densities; the other is based on the logarithm of the mean of densities. We build a statistical model relating microbial count data to the LR parameters, derive maximum likelihood and method of moments estimators for each LR parameter, and compare the estimators according to both their asymptotic characteristics and the results of a simulation study utilizing realistic sample sizes. Standard error formulas for the estimators are derived, and they are evaluated via simulation studies. The results of this investigation lead us to recommend the method of moments estimator, regardless of which de®nition of LR is chosen.en_US
dc.titleEstimating the antimicrobial log reduction: part 1. quantitative assaysen_US
dc.typeArticleen_US
mus.citation.extentfirstpage19en_US
mus.citation.extentlastpage45en_US
mus.citation.journaltitleQuantitative Microbiologyen_US
mus.citation.volume1en_US
mus.identifier.categoryEngineering & Computer Scienceen_US
mus.identifier.doi10.1023/A:1010072226737en_US
mus.relation.collegeCollege of Engineeringen_US
mus.relation.departmentCenter for Biofilm Engineering.en_US
mus.relation.departmentChemical & Biological Engineering.en_US
mus.relation.departmentChemical Engineering.en_US
mus.relation.universityMontana State University - Bozemanen_US
mus.relation.researchgroupCenter for Biofilm Engineering.en_US
mus.data.thumbpage11en_US


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