Sentence examples for bias into the estimation from inspiring English sources

However, such follow-up study is difficult to conduct, as only slightly more than half of patients were included in the follow-up study in the Heilongjiang study, which may have introduced bias into the estimation of the recurrence and death rates, there is also the possibility of unreliable conclusions being drawn from any data that is collected.

To test whether the starting tree introduced bias into the estimation of the partitioning scheme, we used a five-step process.

It is important for researchers to recognise MNAR as it introduces bias into the estimation of associations and parameters of interest.

Nevertheless, the limited number and the small range of environments covered by the current data can be expected to introduce a strong bias into the estimation of the viral DNA fraction.

Time to surgery was computed based on the dates of hospital admission and surgery and was not refined to the actual hour of surgery and to access in the emergency room, which might introduce a bias into the estimation of the operative delay effect.

Such unrepresentative rates could introduce bias into the estimations, because they could be attributable to even small random variations in the number of individuals hospitalized for ACSCs in these small populations, rather than to differences in access to primary health care.

However simulations showed that parsimony-based ancestral assignment can introduce additional biases into the estimation of substitution rates [see Additional File 1].

This can generate problems in calibrating the hydrological model when spatial rainfall localization is not taken into account: a bias in the estimation of parameters makes their physical interpretation difficult and leads to overestimation of extreme flows.

Four important sources of bias in the application of the method were identified: bias related to POF staging, bias in POF ageing, sampling bias and bias in the estimation of spawning fraction.

This selection does not introduce bias in the estimation.

This may constitute a bias in the estimation.