The apparent superiority of sonographic EFW over clinical EFW applies principally to preterm pregnancies. The prediction limitation calculation suggests that either method, for any particular estimate between 500 and 4500 g, has limited value in the estimation of actual birth weight, because this outcome is highly variable and frequently lies outside of the useful bandwidth (+/- 10%) for prospective management.

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In analyzing systems which depend on uncertain parameters, one technique is to partition the uncertain parameter domain into a failure set and its complement, and judge the quality of the system by estimating the probability of failure. If this is done by a sampling technique such as Monte Carlo and the probability of failure is small, accurate approximation can require so many sample points that the computational expense is prohibitive. Previous work of the authors has shown how to bound the failure event by sets of such simple geometry that their probabilities can be calculated analytically. In this paper, it is shown how to make use of these failure bounding sets and conditional sampling within them to substantially reduce the computational burden of approximating failure probability. It is also shown how the use of these sampling techniques improves the confidence intervals for the failure probability estimate for a given number of sample points and how they reduce the number of sample point analyses needed to achieve a given level of confidence.