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While the latter are prone to considerable bias unless the sample size is pretty large – of the order of few thousands at least – the former were shown to be reasonably robust with sample sizes of few hundreds.
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Although Maxent is reasonably robust with respect to covariation, an a priori variable selection process was used to reduce covariation.
We thus find that the connectivity-based criterion for hubs is reasonably robust with respect to random edge deletion and addition.
This suggests that all four methods generate estimates that are reasonably robust with large sample sizes, even where a substantial proportion of the data are missing.
In addition, the analyses of radiation dose with stroke and heart disease mortality showed that the association is reasonably robust with respect to confounding by lifestyle, sociodemographic, or other health factors or misdiagnosis.
The second of these assumptions is clearly violated with the data from Maryland; however the results appear to be reasonably robust to this discrepancy, except in the case of Cumberland.
This chapter introduces a data model that is believed to be reasonably robust even for the most involved applications.
The probabilities of crossover and mutation are also selected experimentally and found to be reasonably robust around the selected values.
The method, however, is known to be reasonably robust against departures from the distributional assumptions.
Therefore the results of the tests for collinearity suggest that the models may be reasonably robust.
To some extent, this suggests that the conventional country-based approach to global health may be reasonably robust.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com