Sentence examples for binomial trials from inspiring English sources

Test statistics and sample size formulae for comparative binomial trials with null hypothesis on non-zero risk difference or non-unity relative risk.

The model was stochastic in that binomial trials governed the random outcomes of host survival and reproduction, transmission, movement between disease classes, and prion survival.

This analysis tests the null hypothesis that successes in a series of binomial trials are randomly distributed.

The chance of observing either 28 or more successes or five or fewer successes in 33 binomial trials is P<0.0001.

The negative binomial distribution supposes there is a sequence of independent Bernoulli trials (or binomial trials), each trial having two potential outcomes called "success" and "failure".

The power to demonstrate a relationship between SNP genotype and OS was estimated using sample size formulae for comparative binomial trials (Farrington and Manning, 1990).

Final source of registration was treated as a binomial trial (case notes or death certificates).

The threshold for the number of microarrays was set by the binomial trial estimate (see Methods).

For each window, a binomial trial (P = 0.01) was used to determine whether the phenotype should be drawn from the null or alternate.

The threshold for the number of microarray experiments whereas we found statistically significant association was set by the binomial trial estimate P (N, k ) = ∑ k N C N k p k (1 − p ) N − k.

The association between the presence of a potential AuxRE and auxin-responsive gene expression was considered as significant, if it was revealed in more than three microarrays, the threshold was set by the binomial trial estimate (See Methods).