Sentence examples for multiple assumptions is from inspiring English sources

The consistency of the conclusions under multiple assumptions is important since standard significance tests are not applicable, due to the complexities of sampling error in the original surveys compounded with survey errors in the access information for the 6 methods.

If multiple assumptions are plausible, the uncertainty among the different options can be characterized through a distribution.

Multiple incorrect assumptions were made about participants, primary care workflows and IT capacity, software vendor user knowledge, and the health IT infrastructure.

Multiple model assumptions are violated due to the fact that values of categorical data are bounded within certain limits e.g. 0 to 1 or 1 to 4. Therefore, generalized linear mixed models (GLMM) such as threshold models can be more appropriate for the analysis of categorical traits since scores are transformed by the model into values on an underlying continuous liability scale.

One difficulty with this assessment of the instrumental variable assumptions is the problem of multiple testing.

In the case of multiple phenotypes (which could also be in multiple strains) the assumption is that the phenotypes are measuring the effect of the same polymorphism between progenitor strains for the cross.

For an approach that makes use of multiple alignments, our assumption is that a non-negligible amount of the existing RNA RNA interaction contains compensatory changes across the binding sites.

This contrasts with the view that multiple approaches with conflicting assumptions are a hindrance.

Since the programme had multiple partners, estimations and assumptions were used to analyze the cost, to differentiate the contribution of UNICEF.

Our assumptions are that multiple independent transfers of a gene would likely result in different gene environments being affected.

A further strength of this analysis was the use of observed patient-level data for modelling multiple health states and, where assumptions were needed, the most conservative option was selected to avoid biasing the model results.