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Decision Trees: Sensitivity Analysis, Deterministic

All decision analyses have to deal with various forms of uncertainty in a manner that informs the decisions being made. In particular, it is essential to establish the degree to which the results of an analysis are sensitive to a change in a parameter or an assumption and the extent to which the conclusions of the analysis are robust to such changes. The assessment of sensitivity or robustness is known as sensitivity analysis. Such an analysis would consider, for example, the fact that the mean length of inpatient hospital stay associated with a particular clinical event is estimated with uncertainty (reflected in its standard error) and would consider how the results of the study would change if a higher or lower value were used for ...

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