Sentence examples for estimated equivalence from inspiring English sources

Quantitative NO measurements are conducted based on the knowledge of attenuation, temperature, the estimated equivalence ratio, and a calibration procedure.

Being based on limited data, the estimated equivalence limits in step L are always uncertain.

For 44 analytes (including 20 with significant differences between GMO and counterpart) equivalence was established in a formal test of equivalence (at the 95% confidence level) using the estimated equivalence limits.

For the French Canadian, Danish, Norwegian and Swedish versions, we estimated equivalence of meaning with the English version quantitatively, and then carried out several further cognitive interviews among bilingual speakers of English and each of the four languages.

In the Method section exact calculations will be defined, and it will be shown that the proposed test E1 applied to estimated equivalence limits is actually just a test of difference, with the null hypothesis that GMO and reference means are equal, but allowing for variability between genotypes (which is the crucial difference with the traditional difference test).

These issues relate to the importance of ensuring that the study is large enough to have sufficient power so that the estimated equivalence effect is estimated with sufficient precision so that possible lack of equivalence can be ruled out (i.e., by the 95 % CI excluding all values indicating measurement non-equivalence).

Further consideration and modelling of the effects of reliability on estimating equivalence is therefore desirable.

Another approach to estimate equivalence class sizes was taken by Golle [ 52], where he assumed a uniform distribution of dates of birth of individuals living in a geographic area in assigning them to equivalence classes.

Lacking this we estimate equivalence limits from field studies with concurrent reference varieties, which are typically the same studies in which also the GMO and its non-GM counterpart are tested.

Several algorithms have been proposed to estimate the equivalence class of a DAG from observational data (Chickering, 2002 , 1996 Dash and Druzdzel, 1999; Madigan et al., 1996; Meek, 1995; Pearl, 2000).

Note that we need the sed GC 1 (so excluding genotypic variation) for the GMO to counterpart difference test D, and the sed GR ;2 (including genotypic variation) for estimating the equivalence limits and test E1.