Sentence examples for misclassification was estimated from inspiring English sources

Using a 10% sample of households as the starting population and parameters for demographic and household changes over 5 years, the extent of contact misclassification was estimated through a simulation model of household dynamics, which traced contact with index cases in households over time.

An overall misclassification rate was estimated by summing the misclassifications for each APACHE II score from this sample.

Owing to the limited number of samples, the misclassification error was estimated by leave-one-out cross-validation (LOOCV).

Based on in-depth case review in the randomly selected subgroup (see later), a 10% misclassification rate was estimated, suggesting the true prevalence within the study period was approximately 1.1% (95% CI 1.0-1.2 1.0-1.2

The predictive accuracy was estimated using misclassification rate, the phi coefficient correlation, sensitivity and specificity.

A misclassification-bias-adjusted relative risk was estimated under a variety of possible fixed sensitivities and specificities of smoking classification among those with and without TJR.

It was estimated that the probability of misclassification of a twin pair was 1.7% [23].

Instead, exposure was estimated based on job titles, work history, or job exposure matrices, possibly resulting in exposure misclassification.

In the previous subsection the misclassification probabilities are estimated based on a small set of replicated surrogate measurements, whose accuracy may be questionable due to the small size of the data.

This misclassification has been estimated to approximately 8 20% in Sweden and the US (Kniffin et al, 1994; Schulman and Lindmarker, 2000).

In practice, misclassification probabilities are usually unavailable and must be estimated from additional data sources.