Sentence examples for insignificant likelihood from inspiring English sources

During P2, the isolation ward had little impact on acquisition rates: the sporadic acquisition rate remained the only statistically significant source of acquisitions in the ward, while transmission from unisolated patients remained unchanged and insignificant (likelihood ratio test, null hypothesis β1 = 0, p-value 0.2).

At the recommended grade 2 cut-point a low sensitivity (8.7%) and insignificant positive likelihood ratio demonstrate a limited rate of LAM test cross-reactivity of pulmonary NTM infection.

The difference between the models with 0.95 and 0.99 was statistically insignificant by the likelihood ratio test.

It is quite clear that the difference in log likelihoods between fitting STA and the reversible process (REV) is often small, and statistically insignificant, based on the likelihood ratio test, while those between NONSTA and STA, and between NONSTA and REV, are often large, and statistically very significant.

25, 26 Second, longitudinal studies suggest that prostate cancer has the potential to be either clinically "significant" or clinically "insignificant" based on the likelihood that the cancer will threaten a person over the course of his natural lifetime.

We find small and statistically insignificant impacts on both the likelihood of being employed and on the monthly salaries graduates earn conditional on being employed.

MITSU has a clear advantage over deterministic algorithms in that it is less likely to converge to insignificant local maxima of the likelihood function owing to the sEM algorithm, improving results.

We also examined the interaction of age with the quadratic term in week (that is age*week*week), however that was insignificant based on the Wald, likelihood, AIC and BIC criteria.

We also examined the interaction of asthmatic/non-asthmatic status with the quadratic term in week (that is asthmatic*week*week) but that was insignificant based on the Wald, likelihood, AIC and BIC criteria.

As noted above, one of the reasons for stochastic variations of EM being generally more successful than EM is that they have the ability to avoid insignificant local maxima of the likelihood function.

Celeux et al. (1995) note that the sEM algorithm is generally more successful than the EM algorithm owing to stochastic perturbations, which allow the sEM algorithm to escape stable fixed points of the EM algorithm such as insignificant local maxima of the likelihood function.