Sentence examples for first-stage data from inspiring English sources

The information contained in the conditional probability of the genotype given the first-stage data and the initial estimates of the parameters of interest is being maximized for efficient selection of the subset.

Pursuit of adaptive design gains at least 20% to more than 30% genomic patient subset power when the genomic biomarker status is readily usable at study initiation, in comparison to when it is explored using the first-stage data of the same clinical trial.

We present two types of adaptive design: (1) the genomic biomarker is developed external to the clinical trial, which is designed for treatment effect inference; and (2) first-stage data are used to explore a genomic biomarker, but statistical inference of treatment effect in the genomically or genetically defined biomarker subset is only performed at the second stage of the same trial.

SNPs rs1000291 had p<0.05 also in the strategy of enhancement of first-stage data.

In the two-stage framework, options included enhancement of replication (second-stage) data and enhancement of first-stage data.

As stated above in the strategy of enhancement of first-stage data, there were 173 such SNPs.

While the proposed flexible approach allows modifications of trial design, sample size, or statistical analysis using the first stage data, there is no need for a complete prespecification of the adaptation rule.

Then, based on the Rao-Blackwell theorem, we derive the uniformly minimum variance unbiased estimator (UMVUE) as the conditional expectation of an unbiased estimator, which in this case is simply the maximum likelihood estimator based only on the first stage data, given the complete sufficient statistic.

All results described in this paper are referred only to second stage data.

During the third stage data is collected and analyzed to confirm and validate model assumptions and parameters.

By projecting the demand for renewable energy and the associated resulting carbon dioxide emissions up to the years 2020 and 2030, the paper applies in a second stage data envelopment analysis (DEA) evaluating the Greek renewable energy policy.