In this paper, two new sampling strategies are proposed to estimate the Morris' screening sensitivity measure and its improved version.
In 1991 Morris proposed an effective screening sensitivity measure to identify the few important factors in models with many factors.
The wide number of parameters that can influence dust source term production is reduced with statistical tools using a combination of screening, sensitivity analysis, and uncertainty analysis.
However, in a first step we would like to present this utopic scenario of perfect screening, in the second step we will analyse the consequences of lower screening sensitivity and reduced coverage.
Then, the improved version of the Morris' screening sensitivity measure is applied to estimate the effects of the epistemic uncertainty of random variables' distribution parameters on the failure probability using the new quasi-random sampling strategy.
δE = Proportional change in lifetime screening sensitivity.
δE = Proportional change in screening sensitivity.
Remarkably, however, infection rates were extremely insensitive to screening sensitivity.
The third submodel is for the screening sensitivity.
E = Baseline screening sensitivity (the sensitivity of the test).
β2 links tumour size (diameter in millimetres) to screening sensitivity, and β3 links PMD to screening sensitivity.
