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Future research should exemplify robust analyses that explicitly acknowledge these issues and address them in a convincing manner.
Thus, multiple counting sessions (MCS) that allow using robust analyses (e.g. unbiased Chao richness estimate) are available.
Using these transfer functions, robust analyses were conducted for MIMO plants by varying corresponding delay and gain ratios of the system.
This approach could allow more robust analyses and enable comparisons of species richness data collected across larger temporal and spatial scales.
We explored trade-offs between numbers of microsatellite loci used for reliable individual identifications and the need for higher capture rates for robust analyses.
Robust analyses involve integrals over high-dimensional spaces that usually must be evaluated numerically by Laplace's method of asymptotic approximation or by Markov Chain Monte Carlo methods.
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Nevertheless, there is growing evidence that robust statistical analyses with covariate adjustment in multiple regression models can help reduce sample size requirements [29].
Such data are critical for robust probabilistic analyses of links between measured deformation and outcomes in term of volcanic activity, but are rarely published.
We therefore conducted simple, robust statistical analyses with strict significance thresholds.
These datasets will also facilitate more robust secondary analyses, such as explorations with alternative genetic models, epistasis and gene-environment interactions.
The particular genes revealed here were, moreover, supported by a combination of validation by qPCR, biological meaning and the use of robust statistical analyses with stringent adjustments.
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CEO of Professional Science Editing for Scientists @ prosciediting.com