Sentence examples for stochastic endpoint from inspiring English sources

Therefore, at least in this example, the uncertainty in treating tumors as a deterministic versus a stochastic endpoint is not as great as the other uncertainties that have been characterized.

For a stochastic quantal endpoint, this equals the expected population incidence of the quantal effect.

For a stochastic quantal endpoint, severity is related to the probability of experiencing the effect (e.g., from 1 to 2% individual probability of cancer).

As with the prototypical implementation of the unified probabilistic framework described above, implementing the calculation of population incidence for a stochastic quantal endpoint (Equation 1) requires an MC simulation.

In the case of a stochastic quantal endpoint, M H is the "individual probability of effect," which, averaged over the population in Equation 15, would be, by definition, equal to the expected population incidence of effect.

The most important conceptual issue that has not yet been resolved is the question of which quantal endpoints should be treated as deterministic or stochastic quantal endpoints.

Calculating population incidence for stochastic quantal endpoints.

MC calculation of population incidence for stochastic quantal endpoints.

Below we discuss two options, briefly indicated as "deterministic" and as "stochastic" quantal endpoints (Slob et al. 2014).

Another conceptual issue related to stochastic quantal endpoints concerns the definition of a toxicologically equivalent effect metric for individual probability of effect (e.g., of malformations or cancer).

For stochastic (quantal) endpoints, M* relates to the individual probability of effect (although in this case, the overall population incidence can be calculated as well, in which case M vanishes).