Sentence examples for measures a random from inspiring English sources

For all four considered outcome measures, a random intercept and random slope model was deemed appropriate.

As we are limited in the number of random effects by the number of repeated measures, a random effect was included only for the linear slope component to describe inter-individual difference in change trajectory [ 38].

Because performing formal stimulation testing of β-cell function is not feasible in a routine clinical setting, and random C-peptide was well correlated with fasting and stimulated measures, a random C-peptide, measured either in blood or urine (25) and preferably taken postprandially, is a practical alternative.

To remove the dependency within the longitudinal data, each of the three intermediate risk factors was summarized into two summary measures, a random intercept and a random slope, using the following mixed effect model: y i 0 was the measurement of risk factor y taken at baseline for patient i; i.e. the time point before medication was given.

Regarding the analysis of repeated measures, a random-effect model (linear or generalied linear) will be considered, as usually proposed, to study the fixed effects group, time points and interaction 'group x time', taking into account between and within subject variability.

We focus on a decentralized estimation problem via a clustered wireless sensor network measuring a random Gaussian source where the clusterheads amplify and forward their received signals (from the intra-cluster sensors) over orthogonal independent stationary Nakagami fading channels to a remote fusion center that reconstructs an estimate of the original source.

In the fake measure, a random half of the similarity scores were computed with Resnik measure, and the other half were 1 or 0, such that the similarity of two genes with the same EC is 0, otherwise it is 1 (the reversed values ensure that the fake measure has low quality).

The IDs were randomized individually within each strata following baseline measures using a random number computer algorithm and balanced for gender in strata with less than 100 employees.

The principal data source for the measures was a random sample of 12 000 patient records drawn from a population of 50 000 during the study period (January 2009 to December 2012).

We used Breiman's method as described in [ 9] to calculate the average Strength (s), the average Correlation and c/s2 as performance measures of a random forest.

We established the reproducibility of our image analysis technique and of the different T1 measures from a random sample of five healthy volunteers and five patients with aortic stenosis.