An Improvement of the Nonparametric Bootstrap Test for the Comparison of the Coefficient of Variations

Amiri, Saeid; Zwanzig, Silvelyn

doi:10.1080/03610918.2010.512693

Cited by 18 publications

(10 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…It was then determined which CVs were statistically bigger than the smallest ones in each type of sample. A permutation test was used [ 16 , 17 ]. There are two versions of this test (BII and BIII) but since the minimum CV is less than 0.6, version BII is the recommended one.…”

Section: Resultsmentioning

confidence: 99%

Variability in gut mucosal secretory IgA in mice along a working day

et al. 2018

View full text Add to dashboard Cite

ObjectiveTo assess the variability of secretory immunoglobulin A (S-IgA) in the lumen and feces of mice along a working day.ResultsMice were maintained under a 12 h light–dark cycle, light period starting at 8 AM. S-IgA was determined in feces and intestinal content (after one or three washes) at three points along the day: at the beginning, in the middle and at the end of the light period (ELP). Significant reduction in the content of S-IgA in the small intestine fluid and in feces was observed at the end of the light cycle, which coincides with the end of a regular working day (8 PM) in any given animal facility. It was also observed that three washes of the small intestine were more effective than one flush to recover a significant higher amount of S-IgA, with the smallest coefficient of variation observed by the ELP. A smaller CV would imply a reduced number of animals needed to achieve the same meaningful results. The results may be useful when designing animal trials for the selection of probiotic candidates based on their capacity of activating S-IgA, since it would imply a more rational use of experimental animals.

show abstract

Section: Resultsmentioning

confidence: 99%

Variability in gut mucosal secretory IgA in mice along a working day

et al. 2018

View full text Add to dashboard Cite

show abstract

“…In this analysis both out-bred immersion and injection trout had larger group sizes (74 and 66 trout respectively) than the isogenic trout treatment group (26 trout) due to limitations in the number of of clonal fish available. Although the statistical tests used were robust against comparing groups with different samples sizes, like any test, reduced sample sizes can impact their statistical power (Amiri and Zwanzig, 2010; Amiri and Zwanzig, 2011). Regardless of the statistical outcome, the finding holds true that there were substantial levels of between-host variation in the isogenic trout treatment groups (coefficient of variation = 200 – 350%).…”

Section: Discussionmentioning

confidence: 99%

“…The variability between groups was therefore compared using the coefficient of variation (CV) , defined here as the standard deviation/mean, making it a unitless parameter. Because the data was not normally distributed, the coefficient of variation of treatment groups was compared using a distribution-free bootstrap method proposed by Amiri and Zwanzig (Amiri and Zwanzig, 2010; Amiri and Zwanzig, 2011). Briefly, the p-value was calculated with the formula #:{T b (Y 1b * ,Y 2b * ) > T(Y 1 ,Y 2 )}/(B+1) .…”

Section: Methodsmentioning

confidence: 99%

“…In all cases, virus quantification occurred on day 3 post-infection when viral load typically peaks in the host (Peñaranda et al, 2009; Troyer et al, 2008). The differences in viral load variation between treatment groups were assessed by comparing coefficients of variation and conducting bootstrap tests (Amiri and Zwanzig, 2010; Amiri and Zwanzig, 2011). …”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Analysis of host genetic diversity and viral entry as sources of between-host variation in viral load

et al. 2012

View full text Add to dashboard Cite

Little is known about the factors that drive the high levels of between-host variation in pathogen burden that are frequently observed in viral infections. Here, two factors thought to impact viral load variability, host genetic diversity and stochastic processes linked with viral entry into the host, were examined. This work was conducted with the aquatic vertebrate virus, Infectious hematopoietic necrosis virus (IHNV), in its natural host, rainbow trout. It was found that in controlled in vivo infections of IHNV, a suggestive trend of reduced between-fish viral load variation was observed in a clonal population of isogenic trout compared to a genetically diverse population of out-bred trout. However, this trend was not statistically significant for any of the four viral genotypes examined, and high levels of fish-to-fish variation persisted even in the isogenic trout population. A decrease in fish-to-fish viral load variation was also observed in virus injection challenges that bypassed the host entry step, compared to fish exposed to the virus through the natural water-borne immersion route of infection. This trend was significant for three of the four virus genotypes examined and suggests host entry may play a role in viral load variability. However, high levels of viral load variation also remained in the injection challenges. Together, these results indicate that although host genetic diversity and viral entry may play some role in between-fish viral load variation, they are not major factors. Other biological and non-biological parameters that may influence viral load variation are discussed.

show abstract

“…F-tests were used to determine significance of fixed effects. Standard deviation in day and mean of peak shedding, as well as the number of days shedding, were analyzed using Levene’s test and a bootstrap method with a bootstrap value of 1000 (Amiri and Zwanzig, 2010,2011; Wargo et al, 2012). …”

Section: Methodsmentioning

confidence: 99%

Replication and shedding kinetics of infectious hematopoietic necrosis virus in juvenile rainbow trout

et al. 2017

View full text Add to dashboard Cite

Viral replication and shedding are key components of transmission and fitness, the kinetics of which are heavily dependent on virus, host, and environmental factors. To date, no studies have quantified the shedding kinetics of infectious hematopoietic necrosis virus (IHNV) in rainbow trout (Oncorhynchus mykiss), or how they are associated with replication, making it difficult to ascertain the transmission dynamics of this pathogen of high agricultural and conservation importance. Here, the replication and shedding kinetics of two M genogroup IHNV genotypes were examined in their naturally co-evolved rainbow trout host. Within host virus replication began rapidly, approaching maximum values by day 3 post-infection, after which viral load was maintained or gradually dropped through day 7. Host innate immune response measured as stimulation of Mx-1 gene expression generally followed within host viral loads. Shedding also began very quickly and peaked within 2 days, defining a generally uniform early peak period of shedding from 1 to 4 days after exposure to virus. This was followed by a post-peak period where shedding declined, such that the majority offish were no longer shedding by day 12 post-infection. Despite similar kinetics, the average shedding rate over the course of infection was significantly lower in mixed compared to single genotype infections, suggesting a competition effect, however, this did not significantly impact the total amount of virus shed. The data also indicated that the duration of shedding, rather than peak amount of virus shed, was correlated with fish mortality. Generally, the majority of virus produced during infection appeared to be shed into the environment rather than maintained in the host, although there was more retention of within host virus during the post-peak period. Viral virulence was correlated with shedding, such that the more virulent of the two genotypes shed more total virus. This fundamental understanding of IHNV shedding kinetics and variation at the individual fish level could assist with management decisions about how to respond to disease outbreaks when they occur.

show abstract

An Improvement of the Nonparametric Bootstrap Test for the Comparison of the Coefficient of Variations

Cited by 18 publications

References 13 publications

Variability in gut mucosal secretory IgA in mice along a working day

Variability in gut mucosal secretory IgA in mice along a working day

Analysis of host genetic diversity and viral entry as sources of between-host variation in viral load

Replication and shedding kinetics of infectious hematopoietic necrosis virus in juvenile rainbow trout

Contact Info

Product

Resources

About