Sentence examples for methodologies are subject from inspiring English sources

All dietary assessment methodologies are subject to measurement error and food diaries are prone to under-reporting.

7 10 This methodology is subject to selection and observer bias, particularly if the observers were not blinded to the hypothesis as may have been the case in these studies.

However, the study of Woollams et al. (2007) on the preservation of word reading in semantic dementia has shown that the methodology is subject to the potential danger of selection artefacts.

Even though response shift measurement is helpful, it should be used as a supplement as the "then-test" methodology is subject to the possible influence of recall bias (i.e. recall of a previous state being influenced by the patient's current state), and this influence should be considered when drawing conclusions (Robling and Hood 2002, Visser et al. 2005, Riddle and Lingard 2007).

Evidence is presented in this paper that the methodology is subject to many uncontrollable errors, that the reaction is the result of multiple factors, and that the size of the reaction is related to the age of the patient and not to the extent of the malignancy.

Two full-scale specimens fabricated based on the proposed design methodology were subjected to the cyclic loading.

The methodology was subjected to a feasibility assessment in a series of case studies across the EU.

3. Scoring, during which each orientation generated by the placement methodology is subjected to scoring in an effort to identify the most favorable orientations.

Far from a consensus having established itself over the last two millennia, the relationships between these methodologies are the subject of increasing debate today.

According to the methodology, images and structures are subject to discretization and transformation prior to quantification.

Furthermore, such methodologies have been subject to errors incumbent within the nature of the protocol i.e. those protocols reliant upon DNA amplification generate biased datasets from which it is difficult to make firm conclusions [ 19].