Sentence examples for fiducial limits from inspiring English sources

The difference between two OID50 values was considered statistically significant if 95% fiducial limits did not overlap.

Differences in efficacy were considered significant when 95% FL (fiducial limits) of LC50 values did not overlap.

The SAS equivalent method was used to calculate the fiducial limits (confidence intervals), assuming normal function distribution and an "all or nothing" response parameter.

An inverse prediction equation: log10 (cell number) = (log10 (photon flux output)−2.27)/1.01 was derived from the regression analysis to obtain estimates of predicted cell numbers, along with their 95% confidence (fiducial) limits, to predict tumor burden from the photon flux output of live animals.

Bt mortality rates denoted with * are significantly different (non-overlapping fiducial limits (FL)) with their respective antibiotic treatment.

Significant differences in LT25 and LT50 values between treatments were determined based on probit values with non-overlapping 95% Fiducial Limits [ 36].

Engineers have experienced difficulty when attempting to use enveloping or high fiducial limit statistical techniques for defining the shock environment by shock spectra.

The permissible upper fiducial limit of CV should not be greater than 10% to ensure the reproducibility of the model which was also fulfilled by the model in this study (CV 4.43%).

It was considered that the vaccine passed the recommendations when its estimated potency was not less than 4.0 IU in the volume recommended for a single human dose and if the lower fiducial limit (p = 0.95) of the estimated potency was not less than 2.0 IU.

The InVesalius Navigator software enables real-time localization and digitization of anatomical structures with fiducial registration errors within the limits recommended by the specialized literature for clinical practice, i.e. below 3 mm [41].

The fiducial argument is controversial, and it is generally agreed that its applicability is limited to particular statistical problems.