Sensitivity Analysis 01
Sensitivity Analysis 01 : (a) In uncertainty analysis, comparison of risk estimates based on the means and upper bounds of the probability distributions of the input variables. [AIHA, 2000: Risk Assessment Principles for the Industrial Hygienist]; (b) A technique that tests the sensitivity of an output variable to the possible variation in the input variables of a given model. The purpose of sensitivity analysis is to quantify the influence of input variables on the output variable and develop bounds on the model output. The sensitivity of the output variable of a given mathematical model depends on the nature of the mathematical relationship of the model (and plausible values of its input variables). For a given model, the sensitivity of the output variable with respect to each input variable is computed, and the sensitivities of all input variables are compared. When computing the sensitivity with respect to a given input variable, all other input variables are held fixed at their nominal vales. Sensitivity can be calculated for a point estimate of an input variable or over a range of an input variable. Varying several input parameters at the same time will often highlight interaction effects in the model which are not obvious during "one at a time" variation. [REAP, 1995: Residential Exposure Assessment Project]; (c) Process of changing one variable while leaving the others constant to determine its effect on the output. This procedure fixes each uncertain quantity at its credible lower and upper bounds (holding all others at their nominal values, such as medians) and computes the results of each combination of values. The results help to identify the variables that have the greatest effect on exposure estimates and help focus further information gathering efforts. [USEPA, 1997b: Exposure Factors Handbook]
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