Sentence examples for predict prevalence from inspiring English sources

Two main designs are considered: lot quality assurance sampling (LQAS) of children from all schools; and a geostatistical design that samples a subset of schools and uses semi-variogram analysis and spatial interpolation to predict prevalence in the remaining unsurveyed schools.

The detailed breakdown of the prevalence in various wards/specialities can help predict prevalence patterns in most acute settings.

To predict prevalence the loess smoother utilizes information from nearby data points (weighting information based on its distance from the prediction point).

The region or neighborhood from which data are drawn to predict prevalence is based on the percentage of data points in the neighborhood and is referred to as the span size.

To combine the evidence of the absence of BSE and low scrapie prevalence, that has been collected by different surveillance systems over a long period of time, a stochastic, flock explicit model was developed to predict prevalence changes in the long run over the next 70 years.

‡ Prevalence ratios compare predicted prevalence in each category with normal weight accurate assessors who had the same participant characteristics.

The risk of HPAI occurrence for each grid was calculated and classified as the highest risk, high risk, medium risk and low risk according to quartile levels for predicted prevalence in the predictive map.

To quantify the uncertainties surrounding the model predictions, we plotted the probability of each prediction location having a prevalence >50%, rather than mean predicted prevalence at each location.

From the prediction models that were developed in this study, we can obtain the predicted prevalence of RDS-obtained without testing, the predicted prevalence of RDS-obtained after testing with the LBC and the predicted prevalence of RDS-obtained after testing with the L/S ratio.

The examination of the TA muscle however confirmed the predicted prevalence of the oxidative phenotype in the SM/J muscle supporting the predictive power of the network analysis.

Using this model, inferences for the distribution of prevalences, mean prevalence in the region, and predicted prevalence of herds in the region (including the predicted probability of zero prevalence) are also available.